Title :
Model-based invariants for 3D vision
Author_Institution :
Inst. of Comput. Sci., Hebrew Univ. of Jerusalem, Israel
Abstract :
A hierarchical representation of the 3D shape of objects that is invariant to affine and rigid 3D transformations is described. Model-based invariant functions of general 3D objects are defined and constructed using this representation. A linear algorithm for invariant structure from motion from a sequence of images is outlined. The model-based invariant functions are used as model-based object recognition operators, operating on raw image features. An efficient invariant implementation of alignment and geometric hashing is discussed
Keywords :
image recognition; image representation; image sequences; invariance; object recognition; 3D objects; 3D shape; 3D transformations; 3D vision; alignment; geometric hashing; hierarchical representation; linear algorithm; model-based invariant functions; model-based object recognition operators; raw image features; Cameras; Computer science; Image converters; Image recognition; Matrix converters; Object recognition; Shape; Transmission line matrix methods;
Conference_Titel :
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-3880-X
DOI :
10.1109/CVPR.1993.341023
