DocumentCode
2585710
Title
Learning 3D object recognition strategies
Author
Draper, Bruce A. ; Riseman, Edward M.
Author_Institution
Dept. of Comput. & Inf. Sci., Massachusetts Univ., Amherst, MA, USA
fYear
1990
fDate
4-7 Dec 1990
Firstpage
320
Lastpage
324
Abstract
The problem of automatically learning knowledge-directed control strategies is considered. In particular, the authors address the problem of learning object-specific recognition strategies from object descriptions and sets of interpreted training images. A separate recognition strategy is developed for every object in the domain. The goal of each recognition strategy is to identify any and all instances of the object in an image, and give the 3-D position (relative to the camera) of each instance. The goal of the learning process is to build a strategy that minimizes the expected cost of recognition, subject to accuracy constraints imposed by the user
Keywords
computer vision; computerised pattern recognition; computerised picture processing; knowledge based systems; learning systems; 3-D position; 3D object recognition strategies; accuracy constraints; automatic learning; camera; interpreted training images; knowledge-directed control strategies; object descriptions; Automatic control; Cameras; Computer vision; Contracts; Costs; Decision trees; Image recognition; Information science; Object recognition; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 1990. Proceedings, Third International Conference on
Conference_Location
Osaka
Print_ISBN
0-8186-2057-9
Type
conf
DOI
10.1109/ICCV.1990.139541
Filename
139541
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