DocumentCode :
2078967
Title :
Efficient indexing techniques for model based sensing
Author :
Wallack, Aaron S. ; Canny, John F.
Author_Institution :
Dept. of Comput. Sci., California Univ., Berkeley, CA, USA
fYear :
1994
fDate :
21-23 Jun 1994
Firstpage :
259
Lastpage :
266
Abstract :
Indexing is a model-based recognition technique, in which unknown objects are identified using lookup tables. Indexing coordinates are extracted from sensed features, and the indexing coordinates specify a table entry containing the object´s identity. Usually, only a small fraction of the possible indexing coordinates correspond to modeled objects, and hash tables are often used to save space. In this paper, we present a new indexing data structure called a tree grid which has two advantages over hash tables. (i) The tree grid preserves spatial ordering, so that nearby indexing entries can be retrieved efficiently (ii) The tree grid compacts the storage size of the table by a factor of as much as two orders of magnitude. k coordinates index an ordering of the interpretations, and 1 coordinate determines the consistent interpretations for objects with k degrees of freedom. We also show that for almost all model sets, 2k+1 indexing coordinates care sufficient to discriminate between two generic models, implying that 2k+1 indexing coordinates specify a unique in interpretation. We have implemented an indexing algorithm for recognizing 3D objects from pairs of image rays using the tree grid technique, and the results are reported
Keywords :
image recognition; table lookup; tree data structures; indexing coordinates; indexing data structure; indexing techniques; lookup tables; model based sensing; model-based recognition; tree grid; Computer instructions; Data structures; Object recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1994. Proceedings CVPR '94., 1994 IEEE Computer Society Conference on
Conference_Location :
Seattle, WA
ISSN :
1063-6919
Print_ISBN :
0-8186-5825-8
Type :
conf
DOI :
10.1109/CVPR.1994.323838
Filename :
323838
Link To Document :
بازگشت