@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 {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.}
}
@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.}
}
@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.}
}
