DocumentCode :
3251985
Title :
Modeling human visual object recognition
Author :
Edelman, Shimon ; Bulthoff, Heinrich H.
Author_Institution :
Dept. of Appl. Math. & Comput. Sci., Weizmann Inst. of Sci., Rehovot, Israel
Volume :
4
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
37
Abstract :
The topics discussed here are network models of object recognition; a computational theory of recognition; psychophysical support for a view-interpolation model: and an open issue, features of recognition. The authors survey a successful replication of central characteristics of performance in 3-D object recognition by a computational model based on interpolation among a number of stored views of each object. Network models of 3-D object recognition based on interpolation among specific stored views behave in several respects similarly to human observers in a number of recognition tasks. Even closer replication of human performance in recognition should be expected, once the issue of the features used to represent object views is resolved
Keywords :
brain models; image recognition; neural nets; visual perception; 3-D object recognition; object recognition; psychophysical support; view-interpolation model; visual object recognition; Biology computing; Computer networks; Computer science; Humans; Image recognition; Image resolution; Interpolation; Mathematical model; Mathematics; Object recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.227292
Filename :
227292
Link To Document :
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