Title :
Recognizing objects using scale space local invariants
Author :
Bruckstein, A.M. ; Rivlin, E. ; Weiss, I.
Author_Institution :
Dept. of Comput. Sci., Israel Inst. of Technol., Haifa, Israel
Abstract :
In this paper we discuss a new approach to invariant signatures for recognizing curves under viewing distortions and partial occlusion. The approach is intended to overcome the ill-posed problem of finding derivatives, on which local invariants usually depend. The basic idea is to use invariant finite differences, with a scale parameter that determines the size of the differencing interval. The scale parameter is allowed to vary so that a “scale space”-like invariant representation of the curve, with larger difference intervals corresponding to larger coarser scales, can be obtained. In this new representation, each traditional local invariant is replaced by a scale-dependent range of invariants. Thus, instead of invariant signature curves we obtain invariant signature surfaces in a 3D invariant “scale space”
Keywords :
edge detection; finite difference methods; image representation; invariance; object recognition; stereo image processing; 3D invariant scale space; curve recognition; distortions; image representation; invariant finite differences; invariant representation; invariant signature surfaces; object recognition; partial occlusion; scale space local invariants; Automation; Computer science; Computer vision; Educational institutions; Finite difference methods; Gaussian processes; Laboratories; Object recognition; Polynomials; Shape;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.546126