Geometric methods in computer vision; Proceedings of the Meeting, San Diego, CA, July 25, 26, 1991
Various papers on geometric methods in computer vision are presented. Individual topics addressed include: mathematical theories of shape and the modeling of perception, free-form shape representation and deformable surfaces, new method for sensor data fusion in machine vision, spatial and temporal surface interpolation using wavelet bases, differential properties from adaptive thin-plate splines, shape metrics from curvature-scale spaced and curvature-tuned smoothing, energy functions for regularization algorithms, direct method for reconstructing shape from shading, coupled depth-slope model based on augmented Lagrangian techniques, physically based and probabilistic models for computer vision, probabilistic modeling of surfaces. Also discussed are: recognition and positioning of rigid objects using algebraic moment invariants, contour estimation using global shape constraints and local forces, recognizing human eyes, face recognition based on depth maps and surface curvature, model-based surface classification, hierarchical decomposition and axial representation of shape, direct computation of geometric features from motion disparities and shading, invariant feature matching in parameter space with application to line features, spatiotemporal curvature measures for flowfield analysis, primary set of characteristic views for 3D objects, image representation by integrating curvatures and Delaunay triangulations, 3D reconstruction using virtual planes and horopters.
- OSTI ID:
- 6225323
- Report Number(s):
- CONF-9107115-; ISBN: 0-8194-0698-8
- Resource Relation:
- Conference: Society of Photo-Optical Instrumentation Engineers (SPIE) meeting, San Diego, CA (United States), 21-26 Jul 1991; Related Information: SPIE Proceedings. Vol. 1570
- Country of Publication:
- United States
- Language:
- English
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