Computer Vision - ECCV '96: Fourth European Conference on Computer Vision, Cambridge, UK, April 14 -18, 1996. Proceedings, Volume I [Paperback]

The European Conference on Computer Vision (ECCV) has established itself as a major event in this exciting and very active field of research and development. These refereed two-volume proceedings include the 123 papers accepted for presentation at the 4th ECCV, held in Cambridge, UK, in April 1996; these papers were selected from a total of 328 submissions and together give a well-balanced reflection of the state of the art in computer vision.
The papers in volume I are grouped in sections on structure from motion; recognition; geometry and stereo; texture and features; tracking; grouping and segmentation; stereo; and recognition, matching, and segmentation.Self-calibration from image triplets.- Parallax geometry of pairs of points for 3D scene analysis.- Euclidean 3D reconstruction from image sequences with variable focal lengths.- Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection.- Rapid object indexing and recognition using enhanced geometric hashing.- Recognition of geons by parametric deformable contour models.- Automatic extraction of generic house roofs from high resolution aerial imagery.- Three dimensional object modeling via minimal surfaces.- Class based reconstruction techniques using singular apparent contours.- Reliable surface reconstruction from multiple range images.- Shape from appearance: A statistical approach to surface shape estimation.- Volumic segmentation using hierarchical representation and triangulated surface.- Oriented projective geometry for computer vision.- Fast computation of the fundamental matrix for an active stereo vision system.- On binocularly viewed occlusion junctions.- Understanding the shape properties of trihedral polyhedra.- Nonlinear scale-space from n-dimensional sieves.- Hierarchical curve reconstruction. Part I: Bifurcation analysis and recovery of smooth curves.- Texture feature coding method for classification of liver sonography.- Local appropriate scale in ló%