Advances in Computer Vision
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Advances in Computer Vision

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Ruzena Bajcsy
486 g
244x170x15 mm

This second Dagstuhl meeting presents the state-of-art in Computer vision
A semidiscrete nonlinear scale-space theory and its relation to the Perona-Malik paradox.- Topological approach to mathematical morphology.- Segmentation by watersheds: definition and parallel implementation.- A graph network for image segmentation.- Associative memory for images by recurrent neural subnetworks.- Optimal models for visual recognition.- Order of points on a line segment.- Subjective contours detection.- Texture feature based interaction maps: potential and limits.- Non-Markov Gibbs image model with almost local pairwise pixel interactions.- Equivalent contraction kernels to build dual irregular pyramids.- Towards a generalized primal sketch.- Categorization through temporal analysis of patterns.- Detection of regions of interest via the Pyramid Discrete Symmetry Transform.- Dense depth maps by active color illumination and image pyramids.- Local and global integration of discrete vector fields.- A new approach to shape from shading.- Recent uniqueness results in shape from shading.- Computation of time-varying motion and structure parameters from real image sequences.- A theory of occlusion in the context of optical flow.- Algebraic method for solution of some best matching problems.- Determining the attitude of planar objects with general curved contours from a single perspective view.- CAD based 3D object recognition on range images.- Dual quaternions for absolute orientation and hand-eye calibration.- Segmentation of behavioral spaces for navigation tasks.- Geometric algebra as a framework for the perception-action cycle.- List of contributors.
Computer vision solutions used to be very specific and difficult to adapt to different or even unforeseen situations. The current development is calling for simple to use yet robust applications that could be employed in various situations. This trend requires the reassessment of some theoretical issues in computer vision. A better general understanding of vision processes, new insights and better theories are needed. The papers selected from the conference staged in Dagstuhl in 1996 to gather scientists from the West and the former eastern-block countries address these goals and cover such fields as 2D images (scale space, morphology, segmentation, neural networks, Hough transform, texture, pyramids), recovery of 3-D structure (shape from shading, optical flow, 3-D object recognition) and how vision is integrated into a larger task-driven framework (hand-eye calibration, navigation, perception-action cycle).

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