@article {12454,
	title = {A Fast Bilinear Structure from Motion Algorithm Using a Video Sequence and Inertial Sensors},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {33},
	year = {2011},
	month = {2011/01//},
	pages = {186 - 193},
	abstract = {In this paper, we study the benefits of the availability of a specific form of additional information-the vertical direction (gravity) and the height of the camera, both of which can be conveniently measured using inertial sensors and a monocular video sequence for 3D urban modeling. We show that in the presence of this information, the SfM equations can be rewritten in a bilinear form. This allows us to derive a fast, robust, and scalable SfM algorithm for large scale applications. The SfM algorithm developed in this paper is experimentally demonstrated to have favorable properties compared to the sparse bundle adjustment algorithm. We provide experimental evidence indicating that the proposed algorithm converges in many cases to solutions with lower error than state-of-art implementations of bundle adjustment. We also demonstrate that for the case of large reconstruction problems, the proposed algorithm takes lesser time to reach its solution compared to bundle adjustment. We also present SfM results using our algorithm on the Google StreetView research data set.},
	keywords = {3D urban modeling, algorithms, Artificial intelligence, CAMERAS, computer vision., Convergence, fast bilinear structure, Google StreetView research data set, Image Interpretation, Computer-Assisted, Image reconstruction, Image sensors, Image sequences, Imaging, Three-Dimensional, inertial sensors, Information Storage and Retrieval, Linear systems, minimization, MOTION, motion algorithm, Motion estimation, multiple view geometry, Pattern Recognition, Automated, Sensors, SfM equations, sparse bundle adjustment algorithm, structure from motion, Three dimensional displays, vertical direction, Video Recording, video sequence, video signal processing},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2010.163},
	author = {Ramachandran, M. and Veeraraghavan,A. and Chellapa, Rama}
}
@conference {12449,
	title = {P2C2: Programmable pixel compressive camera for high speed imaging},
	booktitle = {2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year = {2011},
	month = {2011/06/20/25},
	pages = {329 - 336},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We describe an imaging architecture for compressive video sensing termed programmable pixel compressive camera (P2C2). P2C2 allows us to capture fast phenomena at frame rates higher than the camera sensor. In P2C2, each pixel has an independent shutter that is modulated at a rate higher than the camera frame-rate. The observed intensity at a pixel is an integration of the incoming light modulated by its specific shutter. We propose a reconstruction algorithm that uses the data from P2C2 along with additional priors about videos to perform temporal super-resolution. We model the spatial redundancy of videos using sparse representations and the temporal redundancy using brightness constancy constraints inferred via optical flow. We show that by modeling such spatio-temporal redundancies in a video volume, one can faithfully recover the underlying high-speed video frames from the observed low speed coded video. The imaging architecture and the reconstruction algorithm allows us to achieve temporal super-resolution without loss in spatial resolution. We implement a prototype of P2C2 using an LCOS modulator and recover several videos at 200 fps using a 25 fps camera.},
	keywords = {Brightness, brightness constancy constraint, camera sensor, CAMERAS, compressive video sensing, high speed imaging, high-speed video frames, Image sequences, imaging, imaging architecture, independent shutter, Liquid crystal on silicon, low speed coded video, Modulation, optical flow, P2C2, programmable pixel compressive camera, reconstruction algorithm, sparse representation, Spatial resolution, spatio-temporal redundancies, temporal redundancy, temporal super-resolution, video coding},
	isbn = {978-1-4577-0394-2},
	doi = {10.1109/CVPR.2011.5995542},
	author = {Reddy, D. and Veeraraghavan,A. and Chellapa, Rama}
}
@conference {12445,
	title = {Variable remapping of images from very different sources},
	booktitle = {2011 18th IEEE International Conference on Image Processing (ICIP)},
	year = {2011},
	month = {2011/09/11/14},
	pages = {1501 - 1504},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We present a system which registers image sequences acquired by very different sources, so that multiple views could be transformed to the same coordinates system. This enables the functionality of automatic object identification and confirmation across views and platforms. The capability of the system comes from three ingredients: 1) image context enlargement through temporal integration; 2) robust motion estimation using the G-RANSAC framework with a relaxed correspondence criteria; 3) constrained motion estimation within the G-RANSAC framework. The proposed system has worked successfully on thousands of frames from multiple collections with significant variations in scale and resolution.},
	keywords = {automatic object identification, Buildings, CAMERAS, Conferences, constrained motion estimation, coordinates system, Estimation, G-RANSAC framework, image context enlargement, Image Enhancement, image registration, image sequence registration, Image sequences, Motion estimation, Robustness, temporal integration, variable image remapping},
	isbn = {978-1-4577-1304-0},
	doi = {10.1109/ICIP.2011.6115729},
	author = {Wei Zhang and Yanlin Guo and Meth, R. and Sokoloff, H. and Pope, A. and Strat, T. and Chellapa, Rama}
}
@article {12464,
	title = {Video Pr{\'e}cis: Highlighting Diverse Aspects of Videos},
	journal = {IEEE Transactions on Multimedia},
	volume = {12},
	year = {2010},
	month = {2010/12//},
	pages = {853 - 868},
	abstract = {Summarizing long unconstrained videos is gaining importance in surveillance, web-based video browsing, and video-archival applications. Summarizing a video requires one to identify key aspects that contain the essence of the video. In this paper, we propose an approach that optimizes two criteria that a video summary should embody. The first criterion, {\textquotedblleft}coverage,{\textquotedblright} requires that the summary be able to represent the original video well. The second criterion, {\textquotedblleft}diversity,{\textquotedblright} requires that the elements of the summary be as distinct from each other as possible. Given a user-specified summary length, we propose a cost function to measure the quality of a summary. The problem of generating a précis is then reduced to a combinatorial optimization problem of minimizing the proposed cost function. We propose an efficient method to solve the optimization problem. We demonstrate through experiments (on KTH data, unconstrained skating video, a surveillance video, and a YouTube home video) that optimizing the proposed criterion results in meaningful video summaries over a wide range of scenarios. Summaries thus generated are then evaluated using both quantitative measures and user studies.},
	keywords = {$K$-means, CAMERAS, combinatorial mathematics, combinatorial optimization, Cost function, data compression, Exemplar selection, Image segmentation, Internet, Iron, Length measurement, multimedia systems, Ncut, optimisation, Optimization methods, original video, Permission, shot segmentation, Surveillance, user specified summary length, video précis, Video sharing, video signal processing, Video summarization},
	isbn = {1520-9210},
	doi = {10.1109/TMM.2010.2058795},
	author = {Shroff, N. and Turaga,P. and Chellapa, Rama}
}
@conference {18477,
	title = {Imaging concert hall acoustics using visual and audio cameras},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing, 2008. ICASSP 2008},
	year = {2008},
	month = {2008///},
	pages = {5284 - 5287},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Using a developed real time audio camera, that uses the output of a spherical microphone array beamformer steered in all directions to create central projection to create acoustic intensity images, we present a technique to measure the acoustics of rooms and halls. A panoramic mosaiced visual image of the space is also create. Since both the visual and the audio camera images are central projection, registration of the acquired audio and video images can be performed using standard computer vision techniques. We describe the technique, and apply it to the examine the relation between acoustical features and architectural details of the Dekelbaum concert hall at the Clarice Smith Performing Arts Center in College Park, MD.},
	keywords = {Acoustic imaging, acoustic intensity images, acoustic measurement, Acoustic measurements, Acoustic scattering, acoustic signal processing, acoustical camera, acoustical scene analysis, acquired audio registration, audio cameras, audio signal processing, CAMERAS, central projection, Computer vision, Educational institutions, HUMANS, image registration, Image segmentation, imaging concert hall acoustics, Layout, microphone arrays, panoramic mosaiced visual image, Raman scattering, reverberation, room acoustics, spherical microphone array beamformer, spherical microphone arrays, video image registration, visual cameras},
	isbn = {978-1-4244-1483-3},
	doi = {10.1109/ICASSP.2008.4518852},
	author = {O{\textquoteright}Donovan,A. and Duraiswami, Ramani and Zotkin,Dmitry N}
}
@conference {14207,
	title = {Combining motion from texture and lines for visual navigation},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007. IROS 2007},
	year = {2007},
	month = {2007/11/29/Oct. },
	pages = {232 - 239},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Two novel methods for computing 3D structure information from video for a piecewise planar scene are presented. The first method is based on a new line constraint, which clearly separates the estimation of distance from the estimation of slant. The second method exploits the concepts of phase correlation to compute from the change of image frequencies of a textured plane, distance and slant information. The two different estimates together with structure estimates from classical image motion are combined and integrated over time using an extended Kalman filter. The estimation of the scene structure is demonstrated experimentally in a motion control algorithm that allows the robot to move along a corridor. We demonstrate the efficacy of each individual method and their combination and show that the method allows for visual navigation in textured as well as un-textured environments.},
	keywords = {3D structure information, CAMERAS, Computer vision, extended Kalman filter, Frequency, image frequencies, Image motion analysis, Image texture, Kalman filters, Layout, motion control, Motion estimation, Navigation, Optical computing, phase correlation, piecewise planar scene, Robustness, Simultaneous localization and mapping, Speech processing, textured plane, video signal processing, visual navigation},
	isbn = {978-1-4244-0912-9},
	doi = {10.1109/IROS.2007.4399568},
	author = {Bitsakos,K. and Li Yi and Ferm{\"u}ller, Cornelia}
}
@conference {11985,
	title = {Multiple View Image Reconstruction: A Harmonic Approach},
	booktitle = {IEEE Conference on Computer Vision and Pattern Recognition, 2007. CVPR {\textquoteright}07},
	year = {2007},
	month = {2007/06/17/22},
	pages = {1 - 8},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This paper presents a new constraint connecting the signals in multiple views of a surface. The constraint arises from a harmonic analysis of the geometry of the imaging process and it gives rise to a new technique for multiple view image reconstruction. Given several views of a surface from different positions, fundamentally different information is present in each image, owing to the fact that cameras measure the incoming light only after the application of a low-pass filter. Our analysis shows how the geometry of the imaging is connected to this filtering. This leads to a technique for constructing a single output image containing all the information present in the input images.},
	keywords = {CAMERAS, filtering theory, Geometry, Harmonic analysis, Image reconstruction, imaging process geometry, Information filtering, Joining processes, Low pass filters, low-pass filter, low-pass filters, multiple view image reconstruction, Position measurement, Power harmonic filters, surface reconstruction},
	isbn = {1-4244-1180-7},
	doi = {10.1109/CVPR.2007.383285},
	author = {Domke, J. and Aloimonos, J.}
}
@article {14182,
	title = {A 3D shape constraint on video},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {28},
	year = {2006},
	month = {2006/06//},
	pages = {1018 - 1023},
	abstract = {We propose to combine the information from multiple motion fields by enforcing a constraint on the surface normals (3D shape) of the scene in view. The fact that the shape vectors in the different views are related only by rotation can be formulated as a rank = 3 constraint. This constraint is implemented in an algorithm which solves 3D motion and structure estimation as a practical constrained minimization. Experiments demonstrate its usefulness as a tool in structure from motion providing very accurate estimates of 3D motion.},
	keywords = {3D motion estimation, algorithms, Artificial intelligence, CAMERAS, decoupling translation from rotation, Estimation error, Fluid flow measurement, Image Enhancement, Image Interpretation, Computer-Assisted, Image reconstruction, Imaging, Three-Dimensional, Information Storage and Retrieval, integration of motion fields, Layout, minimisation, Minimization methods, Motion estimation, multiple motion fields, parameter estimation, Pattern Recognition, Automated, Photography, practical constrained minimization, SHAPE, shape and rotation., shape vectors, stability, structure estimation, surface normals, Three-dimensional motion estimation, video 3D shape constraint, Video Recording, video signal processing},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2006.109},
	author = {Hui Ji and Ferm{\"u}ller, Cornelia}
}
@conference {19493,
	title = {Eye of the Beholder: Phone-Based Text-Recognition for the Visually-Impaired},
	booktitle = {2006 10th IEEE International Symposium on Wearable Computers},
	year = {2006},
	month = {2006///},
	pages = {145 - 146},
	abstract = {Blind and visually-impaired people cannot access essential information in the form of written text in our environment (e.g., on restaurant menus, street signs, door labels, product names and instructions, expiration dates). In this paper, we present and evaluate a mobile text-recognition system capable of extracting written information from a wide variety of sources and communicating it on-demand to the user. The user needs no additional hardware except an ordinary, Internet- enabled mobile camera-phone - a device that many visually-impaired individuals already own. This approach fills a gap in assistive technologies for the visually- impaired because it makes users aware of textual information not available to them through any other means.},
	keywords = {CAMERAS, data mining, handicapped aids, Hardware, Image quality, Internet, Land mobile radio cellular systems, Mobile computing, mobile handsets, mobile text-recognition system, Optical character recognition software, phone-based text-recognition, Product safety, Text recognition, visually-impaired},
	author = {Tudor Dumitras and Lee, M. and Quinones, P. and Smailagic, A. and Siewiorek, Dan and Narasimhan, P.}
}
@conference {15061,
	title = {A Time Saving Method for Human Detection in Wide Angle Camera Images},
	booktitle = {Machine Learning and Cybernetics, 2006 International Conference on},
	year = {2006},
	month = {2006/08//},
	pages = {4029 - 4034},
	abstract = {A time-saving method for human detection in an indoor environment in wide angle camera images is presented in this paper, without using time-consuming template operations such as edge detection and morphological operations. It excludes other objects in motion to detect humans including cases of the partial occlusion of humans, rotation of the head and variation of skin colors. This algorithm is applicable where the memory space is limited and the time requirements are strict, such as in an embedded system. The experimental results show that it took about 0.35 seconds to process the algorithm after the scene study time},
	keywords = {CAMERAS, Embedded system, human detection, image recognition, Image segmentation, indoor environment, Motion estimation, time-saving method, wide angle camera images},
	doi = {10.1109/ICMLC.2006.258804},
	author = {Zhuolin Jiang and Li,Shao-Fa and Gao,Dong-Fa}
}
@conference {14224,
	title = {Integration of motion fields through shape},
	booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005},
	volume = {2},
	year = {2005},
	month = {2005/06/20/25},
	pages = {663- 669 vol. 2 - 663- 669 vol. 2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Structure from motion from single flow fields has been studied intensively, but the integration of information from multiple flow fields has not received much attention. Here we address this problem by enforcing constraints on the shape (surface normals) of the scene in view, as opposed to constraints on the structure (depth). The advantage of integrating shape is two-fold. First, we do not need to estimate feature correspondences over multiple frames, but we only need to match patches. Second, the shape vectors in the different views are related only by rotation. This constraint on shape can be combined easily with motion estimation, thus formulating motion and structure estimation from multiple views as a practical constrained minimization problem using a rank-3 constraint. Based on this constraint, we develop a 3D motion technique, which locates through color and motion segmentation, planar patches in the scene, matches patches over multiple frames, and estimates the motion between multiple frames and the shape of the selected scene patches using the image gradients. Experiments evaluate the accuracy of the 3D motion estimation and demonstrate the motion and shape estimation of the technique by super-resolving an image sequence.},
	keywords = {3D motion estimation, Automation, CAMERAS, computational geometry, Computer vision, constrained minimization problem, decoupling translation from rotation, Educational institutions, image colour analysis, image gradients, image resolution, Image segmentation, image sequence, Image sequences, integration of motion fields, Layout, minimisation, Motion estimation, motion field integration, motion segmentation, parameter estimation, planar patches, rank-3 constraint, scene patches, SHAPE, shape and rotation, shape estimation, structure estimation},
	isbn = {0-7695-2372-2},
	doi = {10.1109/CVPR.2005.190},
	author = {Ji,H. and Ferm{\"u}ller, Cornelia}
}
@article {14230,
	title = {Motion segmentation using occlusions},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {27},
	year = {2005},
	month = {2005/06//},
	pages = {988 - 992},
	abstract = {We examine the key role of occlusions in finding independently moving objects instantaneously in a video obtained by a moving camera with a restricted field of view. In this problem, the image motion is caused by the combined effect of camera motion (egomotion), structure (depth), and the independent motion of scene entities. For a camera with a restricted field of view undergoing a small motion between frames, there exists, in general, a set of 3D camera motions compatible with the observed flow field even if only a small amount of noise is present, leading to ambiguous 3D motion estimates. If separable sets of solutions exist, motion-based clustering can detect one category of moving objects. Even if a single inseparable set of solutions is found, we show that occlusion information can be used to find ordinal depth, which is critical in identifying a new class of moving objects. In order to find ordinal depth, occlusions must not only be known, but they must also be filled (grouped) with optical flow from neighboring regions. We present a novel algorithm for filling occlusions and deducing ordinal depth under general circumstances. Finally, we describe another category of moving objects which is detected using cardinal comparisons between structure from motion and structure estimates from another source (e.g., stereo).},
	keywords = {3D motion estimation, algorithms, Artificial intelligence, CAMERAS, Computer vision, Filling, hidden feature removal, Image Enhancement, Image Interpretation, Computer-Assisted, image motion, Image motion analysis, Image segmentation, Layout, MOTION, Motion detection, Motion estimation, motion segmentation, Movement, Object detection, occlusion, occlusions, optical flow, ordinal depth, Pattern Recognition, Automated, Photography, Reproducibility of results, segmentation, Semiconductor device modeling, Sensitivity and Specificity, video analysis., Video Recording},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2005.123},
	author = {Ogale, A. S and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {11975,
	title = {Robust Contrast Invariant Stereo Correspondence},
	booktitle = {Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005. ICRA 2005},
	year = {2005},
	month = {2005/04/18/22},
	pages = {819 - 824},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A stereo pair of cameras attached to a robot will inevitably yield images with different contrast. Even if we assume that the camera hardware is identical, due to slightly different points of view, the amount of light entering the two cameras is also different, causing dynamically adjusted internal parameters such as aperture, exposure and gain to be different. Due to the difficulty of obtaining and maintaining precise intensity or color calibration between the two cameras, contrast invariance becomes an extremely desirable property of stereo correspondence algorithms. The problem of achieving point correspondence between a stereo pair of images is often addressed by using the intensity or color differences as a local matching metric, which is sensitive to contrast changes. We present an algorithm for contrast invariant stereo matching which relies on multiple spatial frequency channels for local matching. A fast global framework uses the local matching to compute the correspondences and find the occlusions. We demonstrate that the use of multiple frequency channels allows the algorithm to yield good results even in the presence of significant amounts of noise.},
	keywords = {Apertures, Calibration, CAMERAS, Computer science, contrast invariance, diffusion, Educational institutions, Frequency, gabor, Hardware, occlusions, Robot vision systems, Robotics and automation, Robustness, stereo},
	isbn = {0-7803-8914-X},
	doi = {10.1109/ROBOT.2005.1570218},
	author = {Ogale, A. S and Aloimonos, J.}
}
@article {14263,
	title = {The Argus eye: a new imaging system designed to facilitate robotic tasks of motion},
	journal = {IEEE Robotics \& Automation Magazine},
	volume = {11},
	year = {2004},
	month = {2004/12//},
	pages = {31 - 38},
	abstract = {This article describes an imaging system that has been designed to facilitate robotic tasks of motion. The system consists of a number of cameras in a network, arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system{\textquoteright}s own motion and, consequently, the estimation of shape models from the individual cameras. The reason is, inherent ambiguities of confusion between translation and rotation disappear. Pairs of cameras may also be arranged in multiple stereo configurations, which provide additional advantages for segmentation. Algorithms for the calibration of the system and the three-dimensional (3-D) motion estimation are provided.},
	keywords = {Argus eye, Calibration, CAMERAS, computational geometry, Design automation, Eyes, image formation, imaging system, Information geometry, Layout, Motion estimation, multiple stereo configurations, panoramic robots, robot vision, Robot vision systems, robotic motion tasks, Robotics and automation, SHAPE, shape model estimation, system calibration},
	isbn = {1070-9932},
	doi = {10.1109/MRA.2004.1371606},
	author = {Baker, P. and Ogale, A. S and Ferm{\"u}ller, Cornelia}
}
@conference {14209,
	title = {Compound eye sensor for 3D ego motion estimation},
	booktitle = {2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings},
	volume = {4},
	year = {2004},
	month = {2004/10/28/Sept.},
	pages = {3712- 3717 vol.4 - 3712- 3717 vol.4},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We describe a compound eye vision sensor for 3D ego motion computation. Inspired by eyes of insects, we show that the compound eye sampling geometry is optimal for 3D camera motion estimation. This optimality allows us to estimate the 3D camera motion in a scene-independent and robust manner by utilizing linear equations. The mathematical model of the new sensor can be implemented in analog networks resulting in a compact computational sensor for instantaneous 3D ego motion measurements in full six degrees of freedom.},
	keywords = {3D camera motion estimation, CAMERAS, compound eye vision sensor, Computer vision, Equations, Eyes, Geometry, Image sensors, Insects, linear equations, Motion estimation, robot vision, Robustness, sampling geometry, Sampling methods, Sensor phenomena and characterization},
	isbn = {0-7803-8463-6},
	doi = {10.1109/IROS.2004.1389992},
	author = {Neumann, J. and Ferm{\"u}ller, Cornelia and Aloimonos, J. and Brajovic,V.}
}
@conference {12034,
	title = {The influence of shape on image correspondence},
	booktitle = {2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004. Proceedings},
	year = {2004},
	month = {2004/09/06/9},
	pages = {945 - 952},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We examine the implications of shape on the process of finding dense correspondence and half-occlusions for a stereo pair of images. The desired property of the depth map is that it should be a piecewise continuous function which is consistent with the images and which has the minimum number of discontinuities. To zeroeth order, piecewise continuity becomes piecewise constancy. Using this approximation, we first discuss an approach for dealing with such a fronto-parallel shapeless world, and the problems involved therein. We then introduce horizontal and vertical slant to create a first order approximation to piecewise continuity. We highlight the fact that a horizontally slanted surface (ie. having depth variation in the direction of the separation of the two cameras) appears horizontally stretched in one image as compared to the other image. Thus, while corresponding two images, N pixels on a scanline in one image may correspond to a different number of pixels M in the other image, which has consequences with regard to sampling and occlusion detection. We also discuss the asymmetry between vertical and horizontal slant, and the central role of nonhorizontal edges in the context of vertical slant. Using experiments, we discuss cases where existing algorithms fail, and how the incorporation of new constraints provides correct results.},
	keywords = {Automation, CAMERAS, Computational modeling, first order approximation, Geometrical optics, hidden feature removal, image sampling, Image segmentation, Layout, occlusion detection, piecewise continuous function, Pixel, SHAPE, Simulated annealing, stereo image processing, surface fitting},
	isbn = {0-7695-2223-8},
	doi = {10.1109/TDPVT.2004.1335418},
	author = {Ogale, A. S and Aloimonos, J.}
}
@conference {12686,
	title = {Robust Bayesian cameras motion estimation using random sampling},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1361 - 1364 Vol.2 - 1361 - 1364 Vol.2},
	abstract = {In this paper, we propose an algorithm for robust 3D motion estimation of wide baseline cameras from noisy feature correspondences. The posterior probability density function of the camera motion parameters is represented by weighted samples. The algorithm employs a hierarchy coarse-to-fine strategy. First, a coarse prior distribution of camera motion parameters is estimated using the random sample consensus scheme (RANSAC). Based on this estimate, a refined posterior distribution of camera motion parameters can then be obtained through importance sampling. Experimental results using both synthetic and real image sequences indicate the efficacy of the proposed algorithm.},
	keywords = {3D, baseline, Bayesian, CAMERAS, cameras;, coarse-to-fine, consensus, density, estimation;, feature, function;, hierarchy, image, images;, importance, matching;, MOTION, posterior, probability, probability;, processing;, random, RANSAC;, real, realistic, sample, sampling;, scheme;, sequences;, stereo, strategy;, synthetic, wide},
	doi = {10.1109/ICIP.2004.1419754},
	author = {Qian, G. and Chellapa, Rama and Qinfen Zheng}
}
@conference {12000,
	title = {Eye design in the plenoptic space of light rays},
	booktitle = {Ninth IEEE International Conference on Computer Vision, 2003. Proceedings},
	year = {2003},
	month = {2003/10/13/16},
	pages = {1160-1167 vol.2 - 1160-1167 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Natural eye designs are optimized with regard to the tasks the eye-carrying organism has to perform for survival. This optimization has been performed by the process of natural evolution over many millions of years. Every eye captures a subset of the space of light rays. The information contained in this subset and the accuracy to which the eye can extract the necessary information determines an upper limit on how well an organism can perform a given task. In this work we propose a new methodology for camera design. By interpreting eyes as sample patterns in light ray space we can phrase the problem of eye design in a signal processing framework. This allows us to develop mathematical criteria for optimal eye design, which in turn enables us to build the best eye for a given task without the trial and error phase of natural evolution. The principle is evaluated on the task of 3D ego-motion estimation.},
	keywords = {3D ego-motion estimation, Assembly, B-splines, Camera design, CAMERAS, captured image, compound eyes, Computer vision, data mining, eye, eye-carrying organism, Eyes, filter optimization, image representation, image resolution, Information geometry, Laboratories, light field reconstruction, light gathering power, light rays, mixed spherical-Cartesian coordinate system, Motion estimation, natural evolution process, natural eye designs, natural image statistics, optical nanotechnology, Optical signal processing, optimal eye design mathematical criteria, Organisms, plenoptic image formation, plenoptic space, plenoptic video geometry, sampling operators, sensory ecology, Signal design, Signal processing, signal processing framework, signal processing tool, square-summable sequences, visual acuity},
	isbn = {0-7695-1950-4},
	doi = {10.1109/ICCV.2003.1238623},
	author = {Neumann, J. and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {14235,
	title = {New eyes for robotics},
	booktitle = {2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings},
	volume = {1},
	year = {2003},
	month = {2003/10/27/31},
	pages = {1018- 1023 vol.1 - 1018- 1023 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This paper describes an imaging system that has been designed to facilitate robotic tasks of motion. The system consists of a number of cameras in a network arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system{\textquoteright}s own motion and consequently the estimation of shape models from the individual cameras. The reason is that inherent ambiguities of confusion between translation and rotation disappear. Pairs of cameras may also be arranged in multiple stereo configurations which provide additional advantages for segmentation. Algorithms for the calibration of the system and the 3D motion estimation are provided.},
	keywords = {3D motion estimation, Argus eye, array signal processing, Birds, Calibration, CAMERAS, Control systems, Eyes, geometric configuration, imaging, imaging system, Layout, Motion estimation, multiple stereo configurations, Robot kinematics, robot vision, Robot vision systems, ROBOTICS, Robotics and automation, SHAPE, shape models},
	isbn = {0-7803-7860-1},
	doi = {10.1109/IROS.2003.1250761},
	author = {Baker, P. and Ogale, A. S and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {12055,
	title = {Polydioptric camera design and 3D motion estimation},
	booktitle = {2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings},
	volume = {2},
	year = {2003},
	month = {2003/06/18/20},
	pages = {II- 294-301 vol.2 - II- 294-301 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Most cameras used in computer vision applications are still based on the pinhole principle inspired by our own eyes. It has been found though that this is not necessarily the optimal image formation principle for processing visual information using a machine. We describe how to find the optimal camera for 3D motion estimation by analyzing the structure of the space formed by the light rays passing through a volume of space. Every camera corresponds to a sampling pattern in light ray space, thus the question of camera design can be rephrased as finding the optimal sampling pattern with regard to a given task. This framework suggests that large field-of-view multi-perspective (polydioptric) cameras are the optimal image sensors for 3D motion estimation. We conclude by proposing design principles for polydioptric cameras and describe an algorithm for such a camera that estimates its 3D motion in a scene independent and robust manner.},
	keywords = {3D motion estimation, Algorithm design and analysis, Application software, CAMERAS, Computer vision, Eyes, field-of-view camera, Image motion analysis, image sampling, image sensor, Image sensors, Layout, light ray, Motion estimation, multiperspective camera, optimal camera, optimal image formation, optimal sampling pattern, pinhole principle, polydioptric camera design, ray space, scene independent estimation, space structure analysis, stereo image processing, visual information processing},
	isbn = {0-7695-1900-8},
	doi = {10.1109/CVPR.2003.1211483},
	author = {Neumann, J. and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {14753,
	title = {User-specified adaptive scheduling in a streaming media network},
	booktitle = {2003 IEEE Conference on Open Architectures and Network Programming},
	year = {2003},
	month = {2003/04/04/5},
	pages = {87 - 96},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In disaster and combat situations, mobile cameras and other sensors transmit real-time data, used by many operators or analysis tools. Unfortunately, in the face of limited, unreliable resources, and varying demands, not all users may be able to get the fidelity they require. This paper describes MediaNet, a distributed stream processing system designed with the above scenarios in mind. Unlike past approaches, MediaNet{\textquoteright}s users can intuitively specify how the system should adapt based on their individual needs. MediaNet uses both local and online global resource scheduling to improve user performance and network utilization, and adapts without requiring underlying support for resource reservations. Performance experiments show that our scheduling algorithm is reasonably fast, and that user performance and network utilization are both significantly improved.},
	keywords = {Adaptive scheduling, CAMERAS, Computer networks, Computer science, distributed stream processing system, Educational institutions, global resource scheduling, Intelligent networks, MediaNet, Mobile computing, network utilization, Process design, Processor scheduling, quality of service, Streaming media, streaming media network, user performance, user-specified adaptive scheduling},
	isbn = {0-7803-7764-8},
	doi = {10.1109/OPNARC.2003.1196376},
	author = {Hicks, Michael W. and Nagarajan,A. and van Renesse,R.}
}
@conference {11904,
	title = {Contour migration: solving object ambiguity with shape-space visual guidance},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {330- 335 vol.1 - 330- 335 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A fundamental problem in computer vision is the issue of shape ambiguity. Simply stated, a silhouette cannot uniquely identify an object or an object{\textquoteright}s classification since many unique objects can present identical occluding contours. This problem has no solution in the general case for a monocular vision system. This paper presents a method for disambiguating objects during silhouette matching using a visual servoing system. This method identifies the camera motion(s) that gives disambiguating views of the objects. These motions are identified through a new technique called contour migration. The occluding contour{\textquoteright}s shape is used to identify objects or object classes that are potential matches for that shape. A contour migration is then determined that disambiguates the possible matches by purposive viewpoint adjustment. The technique is demonstrated using an example set of objects.},
	keywords = {Artificial intelligence, camera motion, CAMERAS, Computer vision, contour migration, Databases, edge detection, Intelligent robots, Laboratories, Machine vision, object ambiguity, Object recognition, pattern matching, Robot vision systems, servomechanisms, SHAPE, shape matching, shape-space visual guidance, silhouette matching, visual servoing},
	isbn = {0-7803-7398-7},
	doi = {10.1109/IRDS.2002.1041410},
	author = {Abd-Almageed, Wael and Smith,C.E.}
}
@conference {14219,
	title = {Eyes from eyes: new cameras for structure from motion},
	booktitle = {Third Workshop on Omnidirectional Vision, 2002. Proceedings},
	year = {2002},
	month = {2002///},
	pages = {19 - 26},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We investigate the relationship between camera design and the problem of recovering the motion and structure of a scene from video data. The visual information that could possibly be obtained is described by the plenoptic function. A camera can be viewed as a device that captures a subset of this function, that is, it measures some of the light rays in some part of the space. The information contained in the subset determines how difficult it is to solve subsequent interpretation processes. By examining the differential structure of the time varying plenoptic function we relate different known and new camera models to the spatiotemporal structure of the observed scene. This allows us to define a hierarchy of camera designs, where the order is determined by the stability and complexity of the computations necessary to estimate structure and motion. At the low end of this hierarchy is the standard planar pinhole camera for which the structure from motion problem is non-linear and ill-posed. At the high end is a new camera, which we call the full field of view polydioptric camera, for which the problem is linear and stable. In between are multiple-view cameras with large fields of view which we have built, as well as catadioptric panoramic sensors and other omni-directional cameras. We develop design suggestions for the polydioptric camera, and based upon this new design we propose a linear algorithm for ego-motion estimation, which in essence combines differential motion estimation with differential stereo.},
	keywords = {Algorithm design and analysis, Camera design, CAMERAS, Design automation, differential stereo, Educational institutions, ego-motion estimation, Eyes, Geometrical optics, IMAGE PROCESSING, Layout, Motion estimation, observed scene, Optical films, polydioptric camera, RETINA},
	isbn = {0-7695-1629-7},
	doi = {10.1109/OMNVIS.2002.1044486},
	author = {Neumann, J. and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {18468,
	title = {Multimodal 3-D tracking and event detection via the particle filter},
	booktitle = {IEEE Workshop on Detection and Recognition of Events in Video, 2001. Proceedings},
	year = {2001},
	month = {2001///},
	pages = {20 - 27},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio data and determining the state or location of a tracked object. We use Bayesian inference and the particle filter for tracking moving objects, using both video data obtained from multiple cameras and audio data obtained using arrays of microphones. The algorithms developed are applied to determining events arising in two fields of application. In the first, the behavior of a flying echo locating bat as it approaches a moving prey is studied, and the events of search, approach and capture are detected. In a second application we describe detection of turn-taking in a conversation between possibly moving participants recorded using a smart video conferencing setup},
	keywords = {algorithms, APPROACH, audio data collection, audio signal processing, Bayesian inference, Bayesian methods, belief networks, CAMERAS, capture, conversation, echo, Educational institutions, Event detection, event occurrence, filtering theory, flying echo locating bat behaviour, Image motion analysis, inference mechanisms, Laboratories, microphone arrays, moving object tracking, moving participants, moving prey, multimodal 3D tracking, multiple cameras, Object detection, particle filter, Particle filters, Particle tracking, Robustness, search, smart video conferencing setup, target tracking, Teleconferencing, tracking filters, turn-taking detection, video data collection, video signal processing},
	isbn = {0-7695-1293-3},
	doi = {10.1109/EVENT.2001.938862},
	author = {Zotkin,Dmitry N and Duraiswami, Ramani and Davis, Larry S.}
}
@conference {14188,
	title = {A spherical eye from multiple cameras (makes better models of the world)},
	booktitle = {Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001},
	volume = {1},
	year = {2001},
	month = {2001///},
	pages = {I-576- I-583 vol.1 - I-576- I-583 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The paper describes an imaging system that has been designed specifically for the purpose of recovering egomotion and structure from video. The system consists of six cameras in a network arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system{\textquoteright}s own motion and consequently the estimation of shape models from the individual cameras. The reason is that inherent ambiguities of confusion between translation and rotation disappear. We provide algorithms for the calibration of the system and 3D motion estimation. The calibration is based on a new geometric constraint that relates the images of lines parallel in space to the rotation between the cameras. The 3D motion estimation uses a constraint relating structure directly to image gradients.},
	keywords = {3D motion estimation, Calibration, camera network, CAMERAS, Computer vision, egomotion recovery, geometric configuration, geometric constraint, image gradients, image sampling, imaging system, Laboratories, Layout, Motion estimation, multiple cameras, Pixel, Robot vision systems, SHAPE, shape models, Space technology, spherical eye, system calibration, video, video cameras, video signal processing, visual sphere sampling},
	isbn = {0-7695-1272-0},
	doi = {10.1109/CVPR.2001.990525},
	author = {Baker, P. and Ferm{\"u}ller, Cornelia and Aloimonos, J. and Pless, R.}
}
@conference {18463,
	title = {An audio-video front-end for multimedia applications},
	booktitle = {2000 IEEE International Conference on Systems, Man, and Cybernetics},
	volume = {2},
	year = {2000},
	month = {2000///},
	pages = {786-791 vol.2 - 786-791 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Applications such as video gaming, virtual reality, multimodal user interfaces and videoconferencing, require systems that can locate and track persons in a room through a combination of visual and audio cues, enhance the sound that they produce, and perform identification. We describe the development of a particular multimodal sensor fusion system that is portable, runs in real time and achieves these objectives. The system employs novel algorithms for acoustical source location, video-based person tracking and overall system control, which are also described},
	keywords = {Acoustic noise, acoustical source location, Application software, audio cues, audio-video front-end, CAMERAS, Computer vision, Microphones, multimedia applications, multimedia systems, multimodal sensor fusion system, multimodal user interfaces, Position measurement, REAL TIME, Real time systems, real-time systems, sensor fusion, sound, Speech recognition, User interfaces, video cameras, video gaming, video-based person tracking, Videoconference, videoconferencing, Virtual reality, visual cues, Working environment noise},
	isbn = {0-7803-6583-6},
	doi = {10.1109/ICSMC.2000.885945},
	author = {Zotkin,Dmitry N and Duraiswami, Ramani and Davis, Larry S. and Haritaoglu,I.}
}
@conference {14232,
	title = {Multi-camera networks: eyes from eyes},
	booktitle = {IEEE Workshop on Omnidirectional Vision, 2000. Proceedings},
	year = {2000},
	month = {2000///},
	pages = {11 - 18},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Autonomous or semi-autonomous intelligent systems, in order to function appropriately, need to create models of their environment, i.e., models of space time. These are descriptions of objects and scenes and descriptions of changes of space over time, that is, events and actions. Despite the large amount of research on this problem, as a community we are still far from developing robust descriptions of a system{\textquoteright}s spatiotemporal environment using video input (image sequences). Undoubtedly, some progress has been made regarding the understanding of estimating the structure of visual space, but it has not led to solutions to specific applications. There is, however, an alternative approach which is in line with today{\textquoteright}s {\textquotedblleft}zeitgeist.{\textquotedblright} The vision of artificial systems can be enhanced by providing them with new eyes. If conventional video cameras are put together in various configurations, new sensors can be constructed that have much more power and the way they {\textquotedblleft}see{\textquotedblright} the world makes it much easier to solve problems of vision. This research is motivated by examining the wide variety of eye design in the biological world and obtaining inspiration for an ensemble of computational studies that relate how a system sees to what that system does (i.e. relating perception to action). This, coupled with the geometry of multiple views that has flourished in terms of theoretical results in the past few years, points to new ways of constructing powerful imaging devices which suit particular tasks in robotics, visualization, video processing, virtual reality and various computer vision applications, better than conventional cameras. This paper presents a number of new sensors that we built using common video cameras and shows their superiority with regard to developing models of space and motion},
	keywords = {Biosensors, CAMERAS, Computer vision, Eyes, Image sequences, intelligent systems, Layout, Machine vision, Robot vision systems, Robustness, Spatiotemporal phenomena, video cameras, Virtual reality},
	isbn = {0-7695-0704-2},
	doi = {10.1109/OMNVIS.2000.853797},
	author = {Ferm{\"u}ller, Cornelia and Aloimonos, J. and Baker, P. and Pless, R. and Neumann, J. and Stuart, B.}
}
@conference {18464,
	title = {Smart videoconferencing},
	booktitle = {2000 IEEE International Conference on Multimedia and Expo, 2000. ICME 2000},
	volume = {3},
	year = {2000},
	month = {2000///},
	pages = {1597-1600 vol.3 - 1597-1600 vol.3},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The combination of acoustical and video processing to achieve a smart audio and video feed from a set of N microphones and M cameras is a task that might conventionally be accomplished by camera persons and control room staff. However, in the context of videoconferencing, this process needs to be performed by control software. We discuss the use of a multi-camera multi-microphone set-up for unattended videoconferencing, and present details of a prototype implementation being developed},
	keywords = {acoustical processing, Automatic control, CAMERAS, computerised control, control software, Control systems, Intelligent sensors, Layout, Microphones, multi-camera multi-microphone set-up, multimedia systems, Protocols, prototype implementation, Prototypes, sensor fusion, smart videoconferencing, Switches, Teleconferencing, unattended videoconferencing, video processing},
	isbn = {0-7803-6536-4},
	doi = {10.1109/ICME.2000.871075},
	author = {Zotkin,Dmitry N and Duraiswami, Ramani and Philomin,V. and Davis, Larry S.}
}
@conference {18311,
	title = {Estimation of composite object and camera image motion},
	booktitle = {The Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999},
	volume = {1},
	year = {1999},
	month = {1999///},
	pages = {190-197 vol.1 - 190-197 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {An approach for estimating composite independent object and camera image motions is proposed. The approach employs spatio-temporal flow models learned through observing typical movements of the object, to decompose image motion into independent object and camera motions. The spatio-temporal flow models of the object motion are represented as a set of orthogonal flow bases that are learned using principal component analysis of instantaneous flow measurements from a stationary camera. These models are then employed in scenes with a moving camera to extract motion trajectories relative to those learned. The performance of the algorithm is demonstrated on several image sequences of rigid and articulated bodies in motion},
	keywords = {articulated bodies, camera image motion, camera image motions, CAMERAS, composite independent object, composite object estimation, Computer vision, Educational institutions, Image sequences, instantaneous flow measurements, Laboratories, Layout, Motion analysis, Motion estimation, motion trajectories, orthogonal flow bases, Principal component analysis, spatio-temporal flow models, tracking, Vehicles},
	isbn = {0-7695-0164-8},
	doi = {10.1109/ICCV.1999.791217},
	author = {Yacoob,Yaser and Davis, Larry S.}
}
@conference {11993,
	title = {Self-calibration from image derivatives},
	booktitle = {Sixth International Conference on Computer Vision, 1998},
	year = {1998},
	month = {1998/01/04/7},
	pages = {83 - 89},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This study investigates the problem of estimating the calibration parameters from image motion fields induced by a rigidly moving camera with unknown calibration parameters, where the image formation is modeled with a linear pinhole-camera model. The equations obtained show the flow to be clearly separated into a component due to the translation and the calibration parameters and a component due to the rotation and the calibration parameters. A set of parameters encoding the latter component are linearly related to the flow, and from these parameters the calibration can be determined. However, as for discrete motion, in the general case it is not possible, to decouple image measurements from two frames only into their translational and rotational component. Geometrically, the ambiguity takes the form of a part of the rotational component being parallel to the translational component, and thus the scene can be reconstructed only up to a projective transformation. In general, for a full calibration at least four successive image frames are necessary with the 3D-rotation changing between the measurements. The geometric analysis gives rise to a direct self-calibration method that avoids computation of optical flow or point correspondences and uses only normal flow measurements. In this technique the direction of translation is estimated employing in a novel way smoothness constraints. Then the calibration parameters are estimated from the rotational components of several flow fields using Levenberg-Marquardt parameter estimation, iterative in the calibration parameters only. The technique proposed does not require calibration objects in the scene or special camera motions and it also avoids the computation of exact correspondence. This makes it suitable for the calibration of active vision systems which have to acquire knowledge about their intrinsic parameters while they perform other tasks, or as a tool for analyzing image sequences in large video databases},
	keywords = {3D-rotation, active vision, Calibration, CAMERAS, discrete motion, Encoding, Equations, image derivatives, image formation, image measurements, Image motion analysis, image motion fields, Image reconstruction, Image sequences, large video databases, Layout, Levenberg-Marquardt parameter estimation, linear pinhole-camera model, Motion estimation, Motion measurement, Optical computing, parameter estimation, projective transformation, rigidly moving camera, self-calibration, smoothness constraints, unknown calibration parameters},
	isbn = {81-7319-221-9},
	doi = {10.1109/ICCV.1998.710704},
	author = {Brodsky, T. and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {14264,
	title = {The confounding of translation and rotation in reconstruction from multiple views},
	booktitle = {, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997. Proceedings},
	year = {1997},
	month = {1997/06/17/19},
	pages = {250 - 256},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {If 3D rigid motion is estimated with some error a distorted version of the scene structure will in turn be computed. Of computational interest are these regions in space where the distortions are such that the depths become negative, because in order to be visible the scene has to lie in front of the image. The stability analysis for the structure-from-motion problem presented in this paper investigates the optimal relationship between the errors in the estimated translational and rotational parameters of a rigid motion, that results in the estimation of a minimum number of negative depth values. The input used is the value of the flow along some direction, which is more general than optic flow or correspondence. For a planar retina it is shown that the optimal configuration is achieved when the projections of the translational and rotational errors on the image plane are perpendicular. Furthermore, the projection of the actual and the estimated translation lie on a line passing through the image center. For a spherical retina given a rotational error, the optimal translation is the correct one, while given a translational error. The optimal rotational error is normal to the translational one at an equal distance from the real and estimated translations. The proofs, besides illuminating the confounding of translation and rotation in structure from motion, have an important application to ecological optics, explaining differences of planar and spherical eye or camera designs in motion and shape estimation},
	keywords = {3D rigid motion, CAMERAS, ecological optics, Error correction, Image motion analysis, Image reconstruction, Layout, Motion analysis, Motion estimation, multiple views, Optical distortion, optimal configuration, optimal rotational error, planar retina, RETINA, rigid motion, ROTATION, scene structure, shape estimation, spherical retina, Stability analysis, structure-from-motion problem, translation},
	isbn = {0-8186-7822-4},
	doi = {10.1109/CVPR.1997.609328},
	author = {Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {12033,
	title = {3D motion representations in visual servo control},
	booktitle = {Proceedings of International Symposium on Computer Vision, 1995},
	year = {1995},
	month = {1995/11/21/23},
	pages = {61 - 66},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A new approach to visual servoing and vision-guided robotics is introduced. This approach uses visual information for autonomous behavior. It amounts to using robust, global spatiotemporal representations easily extracted from the dynamic imagery. Specifically, the geometrical patterns of normal flows are used as the input to the servo mechanism. It is shown that the positions of these patterns are related to the three dimensional motion parameters. By locating the positions of these patterns, we can solve a variety of navigational problems with little computational effort},
	keywords = {3D motion representations, autonomous behavior, CAMERAS, computational effort, Computer vision, dynamic imagery, global spatiotemporal representations, image representation, Mobile robots, motion control, Navigation, navigational problems, Optical computing, Robot kinematics, Robot sensing systems, robot vision, Robot vision systems, Robotics and automation, servomechanisms, Servosystems, Spatiotemporal phenomena, vision-guided robotics, visual information, visual servo control, visual servoing},
	isbn = {0-8186-7190-4},
	doi = {10.1109/ISCV.1995.476978},
	author = {Ferm{\"u}ller, Cornelia and LoongFah Cheong and Aloimonos, J.}
}
@conference {14171,
	title = {The information in the direction of image flow},
	booktitle = {, International Symposium on Computer Vision, 1995. Proceedings},
	year = {1995},
	month = {1995/11/21/23},
	pages = {461 - 466},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {If instead of the full motion field, we consider only the direction of the motion field due to a rigid motion, what can we say about the information regarding the three-dimensional motion? In this paper it is shown that considering as the imaging surface the whole sphere, independently of the scene in view, two different rigid motions cannot give rise to the same directional motion field. If we restrict the image to half of a sphere (or an infinitely large image plane) two different rigid motions with instantaneous translational and rotational velocities (t1, ω1) and (t2, ω2) cannot give rise to the same directional motion field unless the plane through t1 and t2 is perpendicular to the plane through ω1 and ω2 (i.e., (t1{\texttimes}t2){\textperiodcentered}(ω1 {\texttimes}ω2)=0). In addition, in order to give a practical significance to these uniqueness results for the case of a limited field of view we also characterize the locations on the image where the motion vectors due to the different motions must have different directions. If (ω1{\texttimes}ω2){\textperiodcentered}(t1 {\texttimes}t2)=0 and certain additional constraints are met, then the two rigid motions could produce motion fields with the same direction. For this to happen the depth of each corresponding surface has to be within a certain range, defined by a second and a third order surface},
	keywords = {Automation, CAMERAS, Computer vision, Educational institutions, image flow, Image motion analysis, Image sequences, imaging surface, Laboratories, Layout, Motion analysis, Motion estimation, motion field, motion vectors, Optical imaging, rigid motion, rigid motions, three-dimensional motion},
	isbn = {0-8186-7190-4},
	doi = {10.1109/ISCV.1995.477071},
	author = {Brodsky, T. and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@article {12216,
	title = {A miniature pan-tilt actuator: the spherical pointing motor},
	journal = {IEEE Transactions on Robotics and Automation},
	volume = {10},
	year = {1994},
	month = {1994/06//},
	pages = {298 - 308},
	abstract = {A pan-tilt mechanism is a computer-controlled actuator designed to point an object such as a camera sensor. For applications in active vision, a pan-tilt mechanism should be accurate, fast, small, inexpensive and have low power requirements. The authors have designed and constructed a new type of actuator meeting these requirements, which incorporates both pan and tilt into a single, two-degree-of-freedom device. The spherical pointing motor (SPM) consists of three orthogonal motor windings in a permanent magnetic field, configured to move a small camera mounted on a gimbal. It is an absolute positioning device and is run open-loop. The SPM is capable of panning and tilting a load of 15 grams, for example a CCD image sensor, at rotational velocities of several hundred degrees per second with a repeatability of .15{\textdegree}. The authors have also built a miniature camera consisting of a single CCD sensor chip and miniature lens assembly that fits on the rotor of this motor. In this paper, the authors discuss the theory of the SPM, which includes its basic electromagnetic principles, and derive the relationship between applied currents and resultant motor position. The authors present an automatic calibration procedure and discuss open- and closed-loop control strategies. Finally, the authors present the physical characteristics and results of their prototype},
	keywords = {absolute positioning device, active vision, Actuators, Application software, Assembly, automatic calibration, camera sensor, CAMERAS, CCD image sensors, CCD sensor chip, Charge coupled devices, Charge-coupled image sensors, closed-loop control strategies, computerised control, Lenses, Magnetic fields, miniature lens assembly, miniature pan-tilt actuator, open-loop control strategies, orthogonal motor windings, pan-tilt mechanism, Permanent magnet motors, position control, Scanning probe microscopy, spherical pointing motor, two-degree-of-freedom device},
	isbn = {1042-296X},
	doi = {10.1109/70.294205},
	author = {Bederson, Benjamin B. and Wallace,R.S. and Schwartz,E.L.}
}
@conference {12201,
	title = {Control and design of the spherical pointing motor},
	booktitle = {, 1993 IEEE International Conference on Robotics and Automation, 1993. Proceedings},
	year = {1993},
	month = {1993/05/02/6},
	pages = {630-636 vol.2 - 630-636 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A miniature pan-tilt actuator, the spherical pointing motor (SPM) has been built. The SPM is an absolute positioning device, designed to orient a small camera sensor in two degrees-of-rotational-freedom. It is 4 cm{\texttimes}5 cm{\texttimes}6 cm and weighs 160 g. The operating principle of the SPM is to orient a permanent magnet to the magnetic field induced by three orthogonal coils by applying the appropriate ratio of currents to the coils. The open-loop control and design of the SPM are described. Physical characteristics and velocity measurements of the prototype are reported. The SPM is modeled with a simple second order system. Without control, it oscillates substantially when a single impulse is applied. By applying a second impulse without feedback, the oscillation can be reduced by as much as a factor of ten},
	keywords = {absolute positioning device, Actuators, camera sensor, CAMERAS, Coils, electric actuators, electric motors, Magnetic field measurement, Magnetic sensors, Open loop systems, open-loop control, orthogonal coils, pan-tilt actuator, permanent magnet, Permanent magnet motors, Permanent magnets, position control, Scanning probe microscopy, second order system, spherical pointing motor, velocity control, Velocity measurement, velocity measurements},
	isbn = {0-8186-3450-2},
	doi = {10.1109/ROBOT.1993.291888},
	author = {Bederson, Benjamin B. and Wallace,R.S. and Schwartz,E.L.}
}
@conference {12020,
	title = {Exploratory active vision: theory},
	booktitle = {Proceedings of 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1992},
	year = {1992},
	month = {1992/06/15/18},
	pages = {10 - 15},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {An active approach to the integration of shape from x modules-here shape from shading and shape from texture-is proposed. The question of what constitutes a good motion for the active observer is addressed. Generally, the role of the visual system is to provide depth information to an autonomous robot; a trajectory module will then interpret it to determine a motion for the robot, which in turn will affect the visual information received. It is suggested that the motion can also be chosen so as to improve the performance of the visual system},
	keywords = {active observer, Active shape model, active vision, Automation, autonomous robot, CAMERAS, Computer science, Computer vision, depth information, Laboratories, Layout, Mobile robots, Motion analysis, optical flow, Robots, shape from shading, shape from texture, shape from x modules, trajectory module, Visual system},
	isbn = {0-8186-2855-3},
	doi = {10.1109/CVPR.1992.223234},
	author = {Herve,J. -Y and Aloimonos, J.}
}
@article {12051,
	title = {Computing Intrinsic Images.},
	year = {1986},
	month = {1986/08//},
	abstract = {Low level modern computer vision is not domain dependent, but concentrates on problems that correspond to identifiable modules in the human visual system. Several theories have been proposed in the literature for the computation of shape from shading, shape from texture, retinal motion from spatiotemporal derivatives of the image intensity function and the like. The problems with the existing approach are basically the following: (1) The employed assumptions are very strong and so most of the algorithms fail when applied to real images. (2) Usually the constraints from the geometry and the physics of the problem are not enough to guarantee uniqueness of the computed parameters. (3) In most cases the resulting algorithms are not robust, in the sense that if there is a slight error in the input this results in a catastrophic error in the output. In this thesis the problem of machine vision is explored from its basics. A low level mathematical theory is presented for the unique robust computation of intrinsic parameters. The computational aspect of the theory envisages a cooperative highly parallel implementation, bringing in information from five different sources (shading, texture, motion, contour and stereo), to resolve ambiguities and ensure uniqueness and stability of the intrinsic parameters. The problems of shape from texture, shape from shading and motion, visual motion analysis and shape and motion from contour are analyzed in detail.},
	keywords = {*ARTIFICIAL INTELLIGENCE, *COMPUTERS, *IMAGE PROCESSING, *VISION, algorithms, CAMERAS, CATASTROPHIC CONDITIONS, COMPUTATIONS, CYBERNETICS, ERRORS, HUMANS, IMAGES, INTENSITY, LOW LEVEL, MATHEMATICS, MOTION, RETINA, Robots, SHADOWS, SHAPE, TEXTURE, THEORY, THESES.},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA189440},
	author = {Aloimonos, J.}
}
@article {11984,
	title = {Determining the Translation of a Rigidly Moving Surface, without Correspondence,},
	year = {1986},
	month = {1986/01//},
	abstract = {A method is presented for the recovery of the three-dimensional translation of a rigidly moving textured object from its images. The novelty of the method consists of the fact that four cameras are used in order to avoid the solution of the correspondence problem. The method seems to be immune to small noise percentages and to have good behavior when the noise increases. Keywords: Computer vision.},
	keywords = {*IMAGE PROCESSING, *OPTICAL DETECTION, *Translation(Image processing), CAMERAS, Computer vision, COMPUTERS, IMMUNITY., MOTION, MOVING TARGETS, NOISE, OPTICAL DETECTION AND DETECTORS, SURFACES, THREE DIMENSIONAL, VISION},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA179409},
	author = {Aloimonos, J. and Basu, Anup}
}
