@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.}
}
@article {14177,
	title = {Vision and action},
	journal = {Image and Vision Computing},
	volume = {13},
	year = {1995},
	month = {1995/12//},
	pages = {725 - 744},
	abstract = {Our work on active vision has recently focused on the computational modelling of navigational tasks, where our investigations were guided by the idea of approaching vision for behavioural systems in the form of modules that are directly related to perceptual tasks. These studies led us to branch in various directions and inquire into the problems that have to be addressed in order to obtain an overall understanding of perceptual systems. In this paper, we present our views about the architecture of vision systems, about how to tackle the design and analysis of perceptual systems, and promising future research directions. Our suggested approach for understanding behavioural vision to realize the relationships of perception and action builds on two earlier approaches, the Medusa philosophy1 and the Synthetic approach2. The resulting framework calls for synthesizing an artificial vision system by studying vision competences of increasing complexity and, at the same time, pursuing the integration of the perceptual components with action and learning modules. We expect that computer vision research in the future will progress in tight collaboration with many other disciplines that are concerned with empirical approaches to vision, i.e. the understanding of biological vision. Throughout the paper, we describe biological findings that motivate computational arguments which we believe will influence studies of computer vision in the near future.},
	keywords = {active vision, perceptual system design and analysis, vision system architecture},
	isbn = {0262-8856},
	doi = {10.1016/0262-8856(95)98754-H},
	url = {http://www.sciencedirect.com/science/article/pii/026288569598754H},
	author = {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 {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.}
}
@conference {14246,
	title = {Perceptual computational advantages of tracking},
	booktitle = {, 11th IAPR International Conference on Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings},
	year = {1992},
	month = {1992/09/30/Aug-3},
	pages = {599 - 602},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The paradigm of active vision advocates studying visual problems in the form of modules that are directly related to a visual task for observers that are active. It is argued that in many cases when an object is moving in an unrestricted manner (translation and rotation) in the 3D world only the motion{\textquoteright}s translational components are of interest. For a monocular observer, using only the normal flow-the spatiotemporal derivatives of the image intensity function-the authors solve the problem of computing the direction of translation. Their strategy uses fixation and tracking. Fixation simplifies much of the computation by placing the object at the center of the visual field, and the main advantage of tracking is the accumulation of information over time. The authors show how tracking is accomplished using normal flow measurements and use it for two different tasks in the solution process. First, it serves as a tool to compensate for the lack of existence of an optical flow field and thus to estimate the translation parallel to the image plane; and second, it gathers information about the motion component perpendicular to the image plane},
	keywords = {active vision, Automation, Employment, fixation, image intensity function, Image motion analysis, IMAGE PROCESSING, Motion estimation, Nonlinear optics, Optical computing, Optical sensors, parameter estimation, pattern recognition, perceptual computational advantages, spatiotemporal derivatives, Spatiotemporal phenomena, tracking, unrestricted motion, visual flow measurements},
	isbn = {0-8186-2910-X},
	doi = {10.1109/ICPR.1992.201633},
	author = {Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@conference {11960,
	title = {Purposive and qualitative active vision},
	booktitle = {Proceedings of 10th International Conference on Pattern Recognition, 1990},
	volume = {i},
	year = {1990},
	month = {1990/06/16/21},
	pages = {346-360 vol.1 - 346-360 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The traditional view of the problem of computer vision as a recovery problem is questioned, and the paradigm of purposive-qualitative vision is offered as an alternative. This paradigm considers vision as a general recognition problem (recognition of objects, patterns or situations). To demonstrate the usefulness of the framework, the design of the Medusa of CVL is described. It is noted that this machine can perform complex visual tasks without reconstructing the world. If it is provided with intentions, knowledge of the environment, and planning capabilities, it can perform highly sophisticated navigational tasks. It is explained why the traditional structure from motion problem cannot be solved in some cases and why there is reason to be pessimistic about the optimal performance of a structure from motion module. New directions for future research on this problem in the recovery paradigm, e.g., research on stability or robustness, are suggested},
	keywords = {active vision, Automation, brain models, complex visual tasks, Computer vision, environmental knowledge, highly sophisticated navigational tasks, HUMANS, Image reconstruction, intentions, Kinetic theory, Laboratories, Medusa, Motion analysis, Navigation, planning, planning (artificial intelligence), purposive-qualitative vision, recovery problem, Robust stability, Robustness, SHAPE, stability},
	isbn = {0-8186-2062-5},
	doi = {10.1109/ICPR.1990.118128},
	author = {Aloimonos, J.}
}
@article {11994,
	title = {Visual shape computation},
	journal = {Proceedings of the IEEE},
	volume = {76},
	year = {1988},
	month = {1988/08//},
	pages = {899 - 916},
	abstract = {Perceptual processes responsible for computing shape from several cues, including shading, texture, contour, and stereo, are examined. It is noted that these computational problems, as well as that of computing shaping from motion, are ill-posed in the sense of Hadamard. It is suggested that regularization theory can be used along with a priori knowledge to restrict the space of possible solutions, and thus restore the problem{\textquoteright}s well-prosedness. Some alternative methods are outlined, and the idea of active vision is explored briefly in connection with the problem},
	keywords = {a priori knowledge, active vision, computational problems, Computer vision, computing shaping from motion, contour, cues, Focusing, HUMANS, ill posed problems, Machine vision, Psychology, regularization theory, RETINA, sense of Hadamard, shading, SHAPE, space of possible solutions, Stereo vision, Surface texture, TEXTURE, visual shape computation, Visual system},
	isbn = {0018-9219},
	doi = {10.1109/5.5964},
	author = {Aloimonos, J.}
}
