Browsing by Author "Fermuller, Cornelia"
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Item On the Geometry of Visual Correspondence(1998-10-15) Fermuller, Cornelia; Aloimonos, Yiannis(Also cross-refernced as CAR-TR-732) Image displacement fieldsoptical flow fields, stereo disparity fields, normal flow fieldsdue to rigid motion possess a global geometric structure which is independent of the scene in view. Motion vectors of certain lengths and directions are constraine d to lie on the imaging surface at particular loci whose location and form depends solely on the 3D motion parameters. If optical flow fields or stereo disparity fields are considered, then equal vectors are shown to lie on conic sections. Similarly, for normal motion fields, equal vectors lie within regions whose boundaries also constitute conics. By studying various properties of these curves and regions and their relationships, a characterization of the structure of rigid motion fields is given. The go al of this paper is to introduce a concept underlying the global structure of image displacement fields. This concept gives rise to various constraints that could form the basis of algorithms for the recovery of visual information from multiple views.Item Vision and Action(1998-10-15) Fermuller, Cornelia; Aloimonos, Yiannis(Also cross-referenced as CAR-TR-722) 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 behavioral systems in 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 syst ems, about how to tackle the design and analysis of perceptual systems, and promising future research directions. Our suggested approach for understanding behavioral vision to realize the relationship of perception and action builds on two earlier approac hes, the Medusa philosophy 13] and the Synthetic approach [15 The resulting framework calls for synthesizing an artificial vision system by studying vision corr petences of increasing complexity and at the same time pursuing the integration of the percept ual 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 biolo gical 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.