@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}
}
@article {12474,
	title = {Applications of a Simple Characterization of Human Gait in Surveillance},
	journal = {Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on},
	volume = {40},
	year = {2010},
	month = {2010/08//},
	pages = {1009 - 1020},
	abstract = {Applications of a simple spatiotemporal characterization of human gait in the surveillance domain are presented. The approach is based on decomposing a video sequence into x-t slices, which generate periodic patterns referred to as double helical signatures (DHSs). The features of DHS are given as follows: 1) they naturally encode the appearance and kinematics of human motion and reveal geometric symmetries and 2) they are effective and efficient for recovering gait parameters and detecting simple events. We present an iterative local curve embedding algorithm to extract the DHS from video sequences. Two applications are then considered. First, the DHS is used for simultaneous segmentation and labeling of body parts in cluttered scenes. Experimental results showed that the algorithm is robust to size, viewing angles, camera motion, and severe occlusion. Then, the DHS is used to classify load-carrying conditions. By examining various symmetries in DHS, activities such as carrying, holding, and walking with objects that are attached to legs are detected. Our approach possesses several advantages: a compact representation that can be computed in real time is used; furthermore, it does not depend on silhouettes or landmark tracking, which are sensitive to errors in background subtraction stage.},
	keywords = {algorithms, Artificial intelligence, Automated;Photography;Reproducibility of Results;Sensitivity and Specificity;Video Recording;, Biometry, Computer-Assisted;Pattern Recognition, double helical signatures, Gait, gait analysis, human gait, human motion kinematics, HUMANS, Image Enhancement, Image Interpretation, Image motion analysis, iterative local curve embedding algorithm, Object detection, simple spatiotemporal characterization, video sequence, Video surveillance},
	isbn = {1083-4419},
	doi = {10.1109/TSMCB.2010.2044173},
	author = {Yang Ran and Qinfen Zheng and Chellapa, Rama and Strat, T.M.}
}
@article {14921,
	title = {The Maryland Large-Scale Integrated Neurocognitive Architecture},
	year = {2008},
	month = {2008/03//},
	institution = {University of Maryland College Park},
	abstract = {Recent progress in neural computation, high performance computing, neuroscience and cognitive science suggests that an effort to produce a general-purpose, adaptive machine intelligence is likely to yield a qualitatively more powerful system than those currently existing. Here we outline our progress in developing a framework for creating such a large-scale machine intelligence, or neurocognitive architecture that is based on the modularity, dynamics and plasticity of the human brain. We successfully implemented three intermediate-scale parts of such a system, and these are described. Based on this experience, we concluded that for the short term, optimal results would be obtained by using a hybrid design including neural, symbolic AI, and artificial life methods. We propose a three-tiered architecture that integrates these different methods, and describe a prototype mini-Roboscout that we implemented and evaluated based on this architecture. We also examined, via computational experiments, the effectiveness of genetic programming as a design tool for recurrent neural networks, and the speed-up obtained for adaptive neural networks when they are executed on a graphical processing unit. We conclude that the implementation of a large-scale neurocognitive architecture is feasible, and outline a roadmap for proceeding.},
	keywords = {*COMPUTATIONS, *HYBRID SYSTEMS, *NEURAL NETS, *NEUROCOGNITIVE ARCHITECTURE, ADAPTIVE SYSTEMS, Artificial intelligence, BRAIN, Cognition, COMPUTER PROGRAMMING, COMPUTER PROGRAMMING AND SOFTWARE, HYBRID AI, Machine intelligence, MECHANICAL ORGANS, MODULAR CONSTRUCTION, NERVOUS SYSTEM, PE61101E, PLASTIC PROPERTIES, PROCESSING EQUIPMENT, RECURRENT NEURAL NETWORK},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA481261},
	author = {Reggia, James A. and Tagamets,M. and Contreras-Vidal,J. and Jacobs, David W. and Weems,S. and Naqvi,W. and Yang,C.}
}
@article {12544,
	title = {Model Driven Segmentation of Articulating Humans in Laplacian Eigenspace},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {30},
	year = {2008},
	month = {2008/10//},
	pages = {1771 - 1785},
	abstract = {We propose a general approach using Laplacian Eigenmaps and a graphical model of the human body to segment 3D voxel data of humans into different articulated chains. In the bottom-up stage, the voxels are transformed into a high-dimensional (6D or less) Laplacian Eigenspace (LE) of the voxel neighborhood graph. We show that LE is effective at mapping voxels on long articulated chains to nodes on smooth 1D curves that can be easily discriminated, and prove these properties using representative graphs. We fit 1D splines to voxels belonging to different articulated chains such as the limbs, head and trunk, and determine the boundary between splines using the spline fitting error. A top-down probabilistic approach is then used to register the segmented chains, utilizing their mutual connectivity and individual properties. Our approach enables us to deal with complex poses such as those where the limbs form loops. We use the segmentation results to automatically estimate the human body models. While we use human subjects in our experiments, the method is fairly general and can be applied to voxel-based segmentation of any articulated object composed of long chains. We present results on real and synthetic data that illustrate the usefulness of this approach.},
	keywords = {3D voxel data segmentation, algorithms, Anatomic;Pattern Recognition, Artificial intelligence, Automated;Reproducibility of Results;Sensitivity and Specificity;Whole Body Imaging;, Computer simulation, Computer-Assisted;Imaging, curve fitting, Eigenvalues and eigenfunctions, graph theory, human articulation, human body graphical model, human motion analysis, HUMANS, Image Enhancement, Image Interpretation, Image motion analysis, image registration, Image segmentation, Laplace transforms, Laplacian eigenspace transform, model driven segmentation, probability, representative graph, skeleton registration, Smoothing methods, solid modelling, spline fitting error, splines (mathematics), Three-Dimensional;Joints;Models, top-down probabilistic approach, voxel neighborhood graph},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2007.70823},
	author = {Sundaresan, A. and Chellapa, Rama}
}
@article {12036,
	title = {A Language for Human Action},
	journal = {Computer},
	volume = {40},
	year = {2007},
	month = {2007/05//},
	pages = {42 - 51},
	abstract = {Human-centered computing (HCC) involves conforming computer technology to humans while naturally achieving human-machine interaction. In a human-centered system, the interaction focuses on human requirements, capabilities, and limitations. These anthropocentric systems also focus on the consideration of human sensory-motor skills in a wide range of activities. This ensures that the interface between artificial agents and human users accounts for perception and action in a novel interaction paradigm. In turn, this leads to behavior understanding through cognitive models that allow content description and, ultimately, the integration of real and virtual worlds. Our work focuses on building a language that maps to the lower-level sensory and motor languages and to the higher-level natural language. An empirically demonstrated human activity language provides sensory-motor-grounded representations for understanding human actions. A linguistic framework allows the analysis and synthesis of these actions.},
	keywords = {anthropocentric system, artificial agent, Artificial intelligence, cognitive model, Concrete, Databases, human action, human activity language, Human computer interaction, human factors, human sensory-motor skill, human-centered computing, human-machine interaction, HUMANS, Intelligent sensors, linguistic framework, linguistics, Mirrors, Morphology, natural language, natural languages, Neurons, Power system modeling, user interface, User interfaces},
	isbn = {0018-9162},
	doi = {10.1109/MC.2007.154},
	author = {Guerra-Filho,G. and Aloimonos, J.}
}
@book {17768,
	title = {Scalable Uncertainty Management: First International Conference, SUM 2007, Washington, DC, USA, October 10-12, 2007 : Proceedings},
	year = {2007},
	month = {2007/11/14/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This book constitutes the refereed proceedings of the First International Conference on Scalable Uncertainty Management, SUM 2007, held in Washington, DC, USA, in Oktober 2007.The 20 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers address artificial intelligence researchers, database researchers, and practitioners to demonstrate theoretical techniques required to manage the uncertainty that arises in large scale real world applications. The papers deal with the following topics: uncertainty models, probabilistic logics, fuzzy logics, and annotated logics, inconsistency logics, database algebras and calculi, scalable database systems, spatial, temporal, mobile and multimedia databases, as well as implementations, and applications.},
	keywords = {Artificial intelligence, Computers / Information Theory, Computers / Intelligence (AI) \& Semantics, Electronic books, Mathematics / Logic, Uncertainty (Information theory)},
	isbn = {9783540754077},
	author = {Prade,Henri and V.S. Subrahmanian}
}
@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}
}
@article {19661,
	title = {How Multirobot Systems Research will Accelerate our Understanding of Social Animal Behavior},
	journal = {Proceedings of the IEEE},
	volume = {94},
	year = {2006},
	month = {2006/07//},
	pages = {1445 - 1463},
	abstract = {Our understanding of social insect behavior has significantly influenced artificial intelligence (AI) and multirobot systems{\textquoteright} research (e.g., ant algorithms and swarm robotics). In this work, however, we focus on the opposite question: "How can multirobot systems research contribute to the understanding of social animal behavior?" As we show, we are able to contribute at several levels. First, using algorithms that originated in the robotics community, we can track animals under observation to provide essential quantitative data for animal behavior research. Second, by developing and applying algorithms originating in speech recognition and computer vision, we can automatically label the behavior of animals under observation. In some cases the automatic labeling is more accurate and consistent than manual behavior identification. Our ultimate goal, however, is to automatically create, from observation, executable models of behavior. An executable model is a control program for an agent that can run in simulation (or on a robot). The representation for these executable models is drawn from research in multirobot systems programming. In this paper we present the algorithms we have developed for tracking, recognizing, and learning models of social animal behavior, details of their implementation, and quantitative experimental results using them to study social insects},
	keywords = {Acceleration, Animal behavior, ant movement tracking, Artificial intelligence, biology computing, Computer vision, control engineering computing, Insects, Intelligent robots, Labeling, monkey movement tracking, multi-robot systems, multirobot systems, robotics algorithms, Robotics and automation, social animal behavior, social animals, social insect behavior, Speech recognition, tracking},
	isbn = {0018-9219},
	author = {Balch, T. and Dellaert, F. and Feldman, A. and Guillory, A. and Isbell, C.L. and Zia Khan and Pratt, S.C. and Stein, A.N. and Wilde, H.}
}
@article {19662,
	title = {MCMC Data Association and Sparse Factorization Updating for Real Time Multitarget Tracking with Merged and Multiple Measurements},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {28},
	year = {2006},
	month = {2006/12//},
	pages = {1960 - 1972},
	abstract = {In several multitarget tracking applications, a target may return more than one measurement per target and interacting targets may return multiple merged measurements between targets. Existing algorithms for tracking and data association, initially applied to radar tracking, do not adequately address these types of measurements. Here, we introduce a probabilistic model for interacting targets that addresses both types of measurements simultaneously. We provide an algorithm for approximate inference in this model using a Markov chain Monte Carlo (MCMC)-based auxiliary variable particle filter. We Rao-Blackwellize the Markov chain to eliminate sampling over the continuous state space of the targets. A major contribution of this work is the use of sparse least squares updating and downdating techniques, which significantly reduce the computational cost per iteration of the Markov chain. Also, when combined with a simple heuristic, they enable the algorithm to correctly focus computation on interacting targets. We include experimental results on a challenging simulation sequence. We test the accuracy of the algorithm using two sensor modalities, video, and laser range data. We also show the algorithm exhibits real time performance on a conventional PC},
	keywords = {algorithms, approximate inference, Artificial intelligence, auxiliary variable particle filter, Computational efficiency, continuous state space, downdating, Image Enhancement, Image Interpretation, Computer-Assisted, Inference algorithms, Information Storage and Retrieval, laser range scanner, laser range scanner., Least squares approximation, least squares approximations, Least squares methods, linear least squares, Markov chain Monte Carlo, Markov processes, MCMC data association, merged measurements, Monte Carlo methods, Movement, multiple merged measurements, multitarget tracking, particle filter, particle filtering (numerical methods), Particle filters, Pattern Recognition, Automated, probabilistic model, QR factorization, Radar tracking, Rao-Blackwellized, real time multitarget tracking, Reproducibility of results, Sampling methods, Sensitivity and Specificity, sensor fusion, sparse factorization updating, sparse least squares, State-space methods, Subtraction Technique, target tracking, updating},
	isbn = {0162-8828},
	author = {Zia Khan and Balch, T. and Dellaert, F.}
}
@article {12618,
	title = {Robust ego-motion estimation and 3-D model refinement using surface parallax},
	journal = {Image Processing, IEEE Transactions on},
	volume = {15},
	year = {2006},
	month = {2006/05//},
	pages = {1215 - 1225},
	abstract = {We present an iterative algorithm for robustly estimating the ego-motion and refining and updating a coarse depth map using parametric surface parallax models and brightness derivatives extracted from an image pair. Given a coarse depth map acquired by a range-finder or extracted from a digital elevation map (DEM), ego-motion is estimated by combining a global ego-motion constraint and a local brightness constancy constraint. Using the estimated camera motion and the available depth estimate, motion of the three-dimensional (3-D) points is compensated. We utilize the fact that the resulting surface parallax field is an epipolar field, and knowing its direction from the previous motion estimates, estimate its magnitude and use it to refine the depth map estimate. The parallax magnitude is estimated using a constant parallax model (CPM) which assumes a smooth parallax field and a depth based parallax model (DBPM), which models the parallax magnitude using the given depth map. We obtain confidence measures for determining the accuracy of the estimated depth values which are used to remove regions with potentially incorrect depth estimates for robustly estimating ego-motion in subsequent iterations. Experimental results using both synthetic and real data (both indoor and outdoor sequences) illustrate the effectiveness of the proposed algorithm.},
	keywords = {3D model refinement, algorithms, Artificial intelligence, Automated;Subtraction Technique;, Computer-Assisted;Imaging, constant parallax model, depth based parallax model, digital elevation map, epipolar field, Image Enhancement, Image Interpretation, iterative algorithm, iterative methods, Motion estimation, robust ego-motion estimation, smooth parallax field, surface parallax, Three-Dimensional;Information Storage and Retrieval;Pattern Recognition},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2005.864167},
	author = {Agrawal,A. and Chellapa, Rama}
}
@article {19663,
	title = {MCMC-based particle filtering for tracking a variable number of interacting targets},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {27},
	year = {2005},
	month = {2005/11//},
	pages = {1805 - 1819},
	abstract = {We describe a particle filter that effectively deals with interacting targets, targets that are influenced by the proximity and/or behavior of other targets. The particle filter includes a Markov random field (MRF) motion prior that helps maintain the identity of targets throughout an interaction, significantly reducing tracker failures. We show that this MRF prior can be easily implemented by including an additional interaction factor in the importance weights of the particle filter. However, the computational requirements of the resulting multitarget filter render it unusable for large numbers of targets. Consequently, we replace the traditional importance sampling step in the particle filter with a novel Markov chain Monte Carlo (MCMC) sampling step to obtain a more efficient MCMC-based multitarget filter. We also show how to extend this MCMC-based filter to address a variable number of interacting targets. Finally, we present both qualitative and quantitative experimental results, demonstrating that the resulting particle filters deal efficiently and effectively with complicated target interactions.},
	keywords = {algorithms, Animals, Artificial intelligence, Computer simulation, Computer vision, Filtering, filtering theory, HUMANS, Image Enhancement, Image Interpretation, Computer-Assisted, Index Terms- Particle filters, Information Storage and Retrieval, Insects, interacting targets, Markov chain Monte Carlo sampling step, Markov chain Monte Carlo., Markov chains, Markov processes, Markov random field motion, Markov random fields, Models, Biological, Models, Statistical, Monte Carlo Method, Monte Carlo methods, MOTION, Movement, multitarget filter, multitarget tracking, particle filtering, Particle filters, Particle tracking, Pattern Recognition, Automated, Sampling methods, Subtraction Technique, target tracking, Video Recording},
	isbn = {0162-8828},
	author = {Zia Khan and Balch, T. and Dellaert, F.}
}
@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.}
}
@article {12654,
	title = {Statistical bias in 3-D reconstruction from a monocular video},
	journal = {Image Processing, IEEE Transactions on},
	volume = {14},
	year = {2005},
	month = {2005/08//},
	pages = {1057 - 1062},
	abstract = {The present state-of-the-art in computing the error statistics in three-dimensional (3-D) reconstruction from video concentrates on estimating the error covariance. A different source of error which has not received much attention is the fact that the reconstruction estimates are often significantly statistically biased. In this paper, we derive a precise expression for the bias in the depth estimate, based on the continuous (differentiable) version of structure from motion (SfM). Many SfM algorithms, or certain portions of them, can be posed in a linear least-squares (LS) framework Ax=b. Examples include initialization procedures for bundle adjustment or algorithms that alternately estimate depth and camera motion. It is a well-known fact that the LS estimate is biased if the system matrix A is noisy. In SfM, the matrix A contains point correspondences, which are always difficult to obtain precisely; thus, it is expected that the structure and motion estimates in such a formulation of the problem would be biased. Existing results on the minimum achievable variance of the SfM estimator are extended by deriving a generalized Cramer-Rao lower bound. A detailed analysis of the effect of various camera motion parameters on the bias is presented. We conclude by presenting the effect of bias compensation on reconstructing 3-D face models from rendered images.},
	keywords = {3D face models, 3D video reconstruction, algorithms, artifacts, Artificial intelligence, Automated;Signal Processing, bias compensation, bundle adjustment, camera motion estimation, Computer simulation, Computer-Assisted;Imaging, Computer-Assisted;Subtraction Technique;Video Recording;, depth estimate, error covariance estimation, error statistics, generalized Cramer-Rao lower bound, Image Enhancement, Image Interpretation, Image reconstruction, initialization procedures, least squares approximations, linear least-squares framework, monocular video, motion compensation, Motion estimation, statistical bias, Statistical;Pattern Recognition, structure from motion algorithms, Three-Dimensional;Information Storage and Retrieval;Models, video signal processing},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2005.849775},
	author = {Roy-Chowdhury, A.K. and Chellapa, Rama}
}
@article {12698,
	title = {An information theoretic criterion for evaluating the quality of 3-D reconstructions from video},
	journal = {Image Processing, IEEE Transactions on},
	volume = {13},
	year = {2004},
	month = {2004/07//},
	pages = {960 - 973},
	abstract = {Even though numerous algorithms exist for estimating the three-dimensional (3-D) structure of a scene from its video, the solutions obtained are often of unacceptable quality. To overcome some of the deficiencies, many application systems rely on processing more data than necessary, thus raising the question: how is the accuracy of the solution related to the amount of data processed by the algorithm? Can we automatically recognize situations where the quality of the data is so bad that even a large number of additional observations will not yield the desired solution? Previous efforts to answer this question have used statistical measures like second order moments. They are useful if the estimate of the structure is unbiased and the higher order statistical effects are negligible, which is often not the case. This paper introduces an alternative information-theoretic criterion for evaluating the quality of a 3-D reconstruction. The accuracy of the reconstruction is judged by considering the change in mutual information (MI) (termed as the incremental MI) between a scene and its reconstructions. An example of 3-D reconstruction from a video sequence using optical flow equations and known noise distribution is considered and it is shown how the MI can be computed from first principles. We present simulations on both synthetic and real data to demonstrate the effectiveness of the proposed criterion.},
	keywords = {3D reconstruction, algorithms, Artificial intelligence, Automated;Reproducibility of Results;Sensitivity and Specificity;Signal Processing, Computer Graphics, Computer-Assisted;Imaging, Computer-Assisted;Software Validation;Subtraction Technique;Video Recording;, Image Enhancement, Image Interpretation, Image reconstruction, Image sequences, information theoretic criterion, Mutual information, NOISE, noise distribution, optical flow equations, second order moments, statistical analysis, Three-Dimensional;Information Storage and Retrieval;Information Theory;Movement;Pattern Recognition, Video sequences, video signal processing},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2004.827240},
	author = {Roy-Chowdhury, A.K. and Chellapa, Rama}
}
@article {12682,
	title = {Visual tracking and recognition using appearance-adaptive models in particle filters},
	journal = {IEEE Transactions on Image Processing},
	volume = {13},
	year = {2004},
	month = {2004/11//},
	pages = {1491 - 1506},
	abstract = {We present an approach that incorporates appearance-adaptive models in a particle filter to realize robust visual tracking and recognition algorithms. Tracking needs modeling interframe motion and appearance changes, whereas recognition needs modeling appearance changes between frames and gallery images. In conventional tracking algorithms, the appearance model is either fixed or rapidly changing, and the motion model is simply a random walk with fixed noise variance. Also, the number of particles is typically fixed. All these factors make the visual tracker unstable. To stabilize the tracker, we propose the following modifications: an observation model arising from an adaptive appearance model, an adaptive velocity motion model with adaptive noise variance, and an adaptive number of particles. The adaptive-velocity model is derived using a first-order linear predictor based on the appearance difference between the incoming observation and the previous particle configuration. Occlusion analysis is implemented using robust statistics. Experimental results on tracking visual objects in long outdoor and indoor video sequences demonstrate the effectiveness and robustness of our tracking algorithm. We then perform simultaneous tracking and recognition by embedding them in a particle filter. For recognition purposes, we model the appearance changes between frames and gallery images by constructing the intra- and extrapersonal spaces. Accurate recognition is achieved when confronted by pose and view variations.},
	keywords = {adaptive filters, adaptive noise variance, algorithms, appearance-adaptive model, Artificial intelligence, Cluster Analysis, Computer Graphics, Computer simulation, Feedback, Filtering, first-order linear predictor, hidden feature removal, HUMANS, Image Enhancement, Image Interpretation, Computer-Assisted, image recognition, Information Storage and Retrieval, Kinematics, Laboratories, Male, Models, Biological, Models, Statistical, MOTION, Movement, Noise robustness, Numerical Analysis, Computer-Assisted, occlusion analysis, Particle filters, Particle tracking, Pattern Recognition, Automated, Predictive models, Reproducibility of results, robust statistics, Sensitivity and Specificity, Signal Processing, Computer-Assisted, State estimation, statistical analysis, Subtraction Technique, tracking, Training data, visual recognition, visual tracking},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2004.836152},
	author = {Zhou,Shaohua Kevin and Chellapa, Rama and Moghaddam, B.}
}
@article {18892,
	title = {A General Approach to Synthesize Problem-Specific Planners},
	year = {2003},
	month = {2003/10/27/},
	institution = {Department of Computer Science, University of Maryland, College Park},
	abstract = {In this paper, we describe a way to improve the performance of hand-tailorable planners by compiling each domain description into a separate domain-specific planner. We discuss why and when this approach can be useful, and we present experimental results showing that our approach produces significant increases in the speed of planning.},
	keywords = {*PLANNING, *SOFTWARE ENGINEERING, Artificial intelligence, COMPUTER PROGRAMMING AND SOFTWARE, COMPUTER PROGRAMS, Logic, problem solving},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA455023},
	author = {Ilghami,Okhtay and Nau, Dana S.}
}
@conference {11896,
	title = {Kernel snakes: non-parametric active contour models},
	booktitle = {IEEE International Conference on Systems, Man and Cybernetics, 2003},
	volume = {1},
	year = {2003},
	month = {2003/10//},
	pages = {240- 244 vol.1 - 240- 244 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In this paper, a new non-parametric generalized formulation to statistical pressure snakes is presented. We discuss the shortcomings of the traditional pressure snakes. We then introduce a new generic pressure model that alleviates these shortcomings, based on the Bayesian decision theory. Non-parametric techniques are used to obtain the statistical models that drive the snake. We discuss the advantages of using the proposed non-parametric model compared to other parametric techniques. Multi-colored-target tracking is used to demonstrate the performance of the proposed approach. Experimental results show enhanced, real-time performance.},
	keywords = {Active contours, Artificial intelligence, Bayes methods, Bayesian decision theory, Bayesian methods, decision theory, Deformable models, Image edge detection, Image segmentation, Intelligent robots, Kernel, kernel snakes, Laboratories, multicolored target tracking, nonparametric active contour models, nonparametric generalized formulation, nonparametric model, nonparametric statistics, nonparametric techniques, real time performance, Robot vision systems, statistical pressure snakes, target tracking},
	isbn = {0-7803-7952-7},
	doi = {10.1109/ICSMC.2003.1243822},
	author = {Abd-Almageed, Wael and Smith,C.E. and Ramadan,S.}
}
@book {15676,
	title = {Algorithm Engineering and Experiments: 4th International Workshop, Alenex 2002, San Francisco, Ca, Usa, January 4-5. 2002 : Revised Papers},
	year = {2002},
	month = {2002/09/17/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Algorithm Engineering and Experiments, ALENEX 2002, held in San Francisico, CA, USA in January 2002.The 15 revised full papers presented were carefully reviewed and selected from 34 submissions. Among the topics addressed are hewistics for algorithms, combinatorial optimization, searching, graph computation, network optimization, scheduling, computational geometry, sorting, and clustering algorithms.},
	keywords = {Architecture / General, Artificial intelligence, Computer algorithms, Computer algorithms/ Congresses, COMPUTERS, Computers / Computer Graphics, Computers / Computer Science, Computers / Data Modeling \& Design, Computers / Data Processing, Computers / General, Computers / Programming / Algorithms, Electronic books, Mathematics / Discrete Mathematics, Medical / General},
	isbn = {9783540439776},
	author = {Mount, Dave and Stein,Clifford}
}
@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 {11899,
	title = {Mixture models for dynamic statistical pressure snakes},
	booktitle = {16th International Conference on Pattern Recognition, 2002. Proceedings},
	volume = {2},
	year = {2002},
	month = {2002///},
	pages = {721- 724 vol.2 - 721- 724 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This paper introduces a new approach to statistical pressure snakes. It uses statistical modeling for both object and background to obtain a more robust pressure model. The Expectation Maximization (EM) algorithm is used to model the data into a Mixture of Gaussians (MoG). Bayesian theory is then employed as a decision making mechanism. Experimental results using the traditional pressure model and the new mixture pressure model demonstrate the effectiveness of the new models.},
	keywords = {active contour models, Active contours, Artificial intelligence, Bayes methods, Bayesian methods, Bayesian theory, complex colored object, Computer vision, decision making, decision making mechanism, dynamic statistical pressure snakes, Equations, expectation maximization algorithm, Gaussian distribution, image colour analysis, Image edge detection, Image segmentation, Intelligent robots, mixture models, mixture of Gaussians, mixture pressure model, Robot vision systems, robust pressure model, Robustness, segmentation results, statistical analysis, statistical modeling},
	isbn = {0-7695-1695-X},
	doi = {10.1109/ICPR.2002.1048404},
	author = {Abd-Almageed, Wael and Smith,C.E.}
}
@article {15473,
	title = {Hierarchical GUI test case generation using automated planning},
	journal = {Software Engineering, IEEE Transactions on},
	volume = {27},
	year = {2001},
	month = {2001/02//},
	pages = {144 - 155},
	abstract = {The widespread use of GUIs for interacting with software is leading to the construction of more and more complex GUIs. With the growing complexity come challenges in testing the correctness of a GUI and its underlying software. We present a new technique to automatically generate test cases for GUIs that exploits planning, a well-developed and used technique in artificial intelligence. Given a set of operators, an initial state, and a goal state, a planner produces a sequence of the operators that will transform the initial state to the goal state. Our test case generation technique enables efficient application of planning by first creating a hierarchical model of a GUI based on its structure. The GUI model consists of hierarchical planning operators representing the possible events in the GUI. The test designer defines the preconditions and effects of the hierarchical operators, which are input into a plan-generation system. The test designer also creates scenarios that represent typical initial and goal states for a GUI user. The planner then generates plans representing sequences of GUI interactions that a user might employ to reach the goal state from the initial state. We implemented our test case generation system, called Planning Assisted Tester for Graphical User Interface Systems (PATHS) and experimentally evaluated its practicality and effectiveness. We describe a prototype implementation of PATHS and report on the results of controlled experiments to generate test cases for Microsoft{\textquoteright}s WordPad},
	keywords = {Artificial intelligence, automated planning, automatic test case generation, Automatic testing, correctness testing, goal state, Graphical user interfaces, hierarchical GUI test case generation, initial state, Microsoft WordPad, operators, plan-generation system, planning (artificial intelligence), Planning Assisted Tester for Graphical User Interface Systems, program testing, software},
	isbn = {0098-5589},
	doi = {10.1109/32.908959},
	author = {Memon, Atif M. and Pollack,M. E and Soffa,M. L}
}
@book {15513,
	title = {Logic-Based Artificial Intelligence},
	year = {2000},
	month = {2000/12/01/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This landmark volume represents the culmination of over 40 years of research in the use of logic as a basis for representing and manipulating problems in the field of artificial intelligence. The use of logic as a basis for commonsense reasoning was started by John McCarthy in 1959. The collection consists of both original research and surveys of almost every subject that uses logic in AI, contributed by leading scientists, and grew out of preliminary work presented at the Workshop on Logic-Based Artificial Intelligence held in Washington, DC, June 1999. All papers have been extensively refereed and revised.  The introductory article presents background on research that has transpired since 1959 and discusses the significance of each chapter in this context. The topics covered in the book are commonsense reasoning, knowledge representation, nonmonotonic reasoning, logic for causation and actions, planning and problem solving, cognitive robotics, logic for agents and actions, inductive reasoning, possibilistic logic, logic and beliefs, logic and language, computational logic, knowledge base system implementations, and applications of theorem proving and logic programming.  Logic-Based Artificial Intelligence is invaluable to graduate students and researchers in artificial intelligence, and advanced methods for database and knowledge base systems. Logic-Based Artificial Intelligence will also be of interest to those applying theorem proving methods to problems in program and hardware verification, to those who deal with large knowledge base systems, those developing cognitive robotics, and for those interested in the solution of McCarthy{\textquoteright}s 1959 "oldest planning problem in AI: getting from home to the airport".},
	keywords = {Artificial intelligence, COMPUTER LOGIC, Computers / Computer Science, Computers / Intelligence (AI) \& Semantics, Logic, Symbolic and mathematical, Mathematics / Logic, Medical / General},
	isbn = {9780792372240},
	author = {Minker, Jack}
}
@conference {17386,
	title = {Supporting creativity with powerful composition tools for artifacts and performances},
	booktitle = {Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 2000},
	year = {2000},
	month = {2000/01/04/7},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Modern software such as word processors, slide preparation/presentation tools, or music composition packages are designed to produce artifacts or performances. Now, some designers are expanding their goals to include creativity support into their software. This essay builds on the genex framework for creativity, which has four phases and eight activities. It focuses on the composition activity by considering tools to support initiation, revision, and evaluation. Some existing tools provide partial support that suggests ways in which to develop more ambitious low, middle, and high level tools. The goal is to enable more people to be more creative more of the time.},
	keywords = {artifacts, Artificial intelligence, composition tools, Computer science, Context modeling, creativity, creativity support, Educational institutions, Information retrieval, Laboratories, Manufacturing, music composition, performances, Software design, software libraries, software tools, US Department of Transportation},
	isbn = {0-7695-0493-0},
	doi = {10.1109/HICSS.2000.926896},
	author = {Shneiderman, Ben}
}
@conference {15467,
	title = {Using a goal-driven approach to generate test cases for GUIs},
	booktitle = {Software Engineering, 1999. Proceedings of the 1999 International Conference on},
	year = {1999},
	month = {1999/05//},
	pages = {257 - 266},
	abstract = {The widespread use of GUIs for interacting with software is leading to the construction of more and more complex GUIs. With the growing complexity comes challenges in testing the correctness of a GUI and the underlying software. We present a new technique to automatically generate test cases for GUIs that exploits planning, a well developed and used technique in artificial intelligence. Given a set of operators, an initial state and a goal state, a planner produces a sequence of the operators that will change the initial state to the goal state. Our test case generation technique first analyzes a GUI and derives hierarchical planning operators from the actions in the GUI. The test designer determines the preconditions and effects of the hierarchical operators, which are then input into a planning system. With the knowledge of the GUI and the way in which the user will interact with the GUI, the test designer creates sets of initial and goal states. Given these initial and final states of the GUI, a hierarchical planner produces plans, or a set of test cases, that enable the goal state to be reached. Our technique has the additional benefit of putting verification commands into the test cases automatically. We implemented our technique by developing the GUI analyzer and extending a planner. We generated test cases for Microsoft{\textquoteright}s Word-Pad to demonstrate the viability and practicality of the approach.},
	keywords = {Artificial intelligence, automatic test case generation, goal state, goal-driven approach, Graphical user interfaces, GUIs, hierarchical planning operators, initial state, Microsoft Word-Pad, operators, planning (artificial intelligence), program testing, software, verification commands},
	author = {Memon, Atif M. and Pollack,M. E and Soffa,M. L}
}
@book {13298,
	title = {Image Analysis and Processing: 8th International Conference, Iciap {\textquoteright}95, San Remo, Italy, September 13-15, 1995 : Proceedings},
	year = {1995},
	month = {1995/09/28/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This book presents the proceedings of the 8th International Conference on Image Analysis and Processing, ICIAP {\textquoteright}95, held in Sanremo, Italy in September 1995 under the sponsorship of the International Association of Pattern Recognition IAPR.The volume presents 108 papers selected from more than 180 submissions together with six invited contributions. The papers are written by a total of 265 contributing authors and give a comprehensive state-of-the-art report on all current issues of image analysis and processing. Theoretical aspects are addressed as well as systems design and advanced applications, particularly in medical imaging.},
	keywords = {Artificial intelligence, COMPUTER AIDED DESIGN, Computer Graphics, Computer science, Computer vision, Computers / CAD-CAM, Computers / Computer Graphics, Computers / Computer Science, Computers / Computer Vision \& Pattern Recognition, Computers / Image Processing, Computers / Intelligence (AI) \& Semantics, Computers / Optical Data Processing, Computers / Software Development \& Engineering / General, Electronic books, IMAGE PROCESSING, Image processing/ Congresses, Imaging systems, Optical data processing, Optical pattern recognition, software engineering},
	isbn = {9783540602989},
	author = {Braccini,Carlo and De Floriani, Leila and Vernazza,Gianni}
}
@article {16988,
	title = {Beyond intelligent machines: just do it},
	journal = {IEEE Software},
	volume = {10},
	year = {1993},
	month = {1993/01//},
	pages = {100 - 103},
	abstract = {The author argues that users want a sense of direct and immediate control over computers that differs from how they interact with people. He presents several examples of these predictable and controllable interfaces developed in the lab. The examples include tree maps and dynamic queries.<>},
	keywords = {Artificial intelligence, Computer aided instruction, Computer errors, controllable interfaces, Displays, dynamic queries, Educational institutions, History, HUMANS, intelligent machines, learning systems, Machine intelligence, predictable interfaces, Speech recognition, tree maps, User interfaces},
	isbn = {0740-7459},
	doi = {10.1109/52.207235},
	author = {Shneiderman, Ben}
}
@article {16323,
	title = {Learning from examples: generation and evaluation of decision trees for software resource analysis},
	journal = {IEEE Transactions on Software Engineering},
	volume = {14},
	year = {1988},
	month = {1988/12//},
	pages = {1743 - 1757},
	abstract = {A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for one problem domain, specifically, that of software resource data analysis. The purpose of the decision trees is to identify classes of objects (software modules) that had high development effort, i.e. in the uppermost quartile relative to past data. Sixteen software systems ranging from 3000 to 112000 source lines have been selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4700 objects, capture a multitude of information about the objects: development effort, faults, changes, design style, and implementation style. A total of 9600 decision trees are automatically generated and evaluated. The analysis focuses on the characterization and evaluation of decision tree accuracy, complexity, and composition. The decision trees correctly identified 79.3\% of the software modules that had high development effort or faults, on the average across all 9600 trees. The decision trees generated from the best parameter combinations correctly identified 88.4\% of the modules on the average. Visualization of the results is emphasized, and sample decision trees are included},
	keywords = {Analysis of variance, Artificial intelligence, Classification tree analysis, Data analysis, decision theory, Decision trees, Fault diagnosis, Information analysis, machine learning, metrics, NASA, production environment, software engineering, software modules, software resource analysis, Software systems, Termination of employment, trees (mathematics)},
	isbn = {0098-5589},
	doi = {10.1109/32.9061},
	author = {Selby,R. W and Porter, Adam}
}
@article {15970,
	title = {Uniform accountability for multiple modes of reasoning},
	journal = {International Journal of Approximate Reasoning},
	volume = {2},
	year = {1988},
	month = {1988/07//},
	pages = {233 - 246},
	abstract = {This article discusses various issues surrounding the general debate on knowledge representation methods and argues in favor of the idea that while many methods are necessary, there also must be a kind of unified nature to the enterprise if it is to serve the needs of intelligence. Specific points include the misleading distinction between probabilistic and logical reasoning regarding the notion of truth and also some matters of nonmonotonicity. An effort is made to sample the broad range of approaches in the literature, with an eye toward such a unification.},
	keywords = {Artificial intelligence, commonsense reasoning, probabilistic logic, probability theory, uncertainty representation},
	isbn = {0888-613X},
	doi = {16/0888-613X(88)90119-3},
	url = {http://www.sciencedirect.com/science/article/pii/0888613X88901193},
	author = {Kanal,Laveen and Perlis, Don}
}
