Invariant object detection based on evidence accumulation and Gabor features

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In this paper. we propose an invariant object detection method based on evidence accumulation and the Gabor transforms feature. In contrast to conventional evidence accumulation methods, the proposed method uses Gabor transform features to detect object parts. Experimental results prove that our algorithm robustly detects arbitrary shaped objects in cluttered environments with invariance to translation, rotation, scaling and small deformation. (C) 2001 Elsevier Science B.V. All rights reserved.
Publisher
Elsevier BV
Issue Date
2001-06
Language
English
Article Type
Article
Keywords

FACE RECOGNITION; HOUGH TRANSFORM; POSE; SHAPES

Citation

PATTERN RECOGNITION LETTERS, v.22, no.8, pp.869 - 882

ISSN
0167-8655
URI
http://hdl.handle.net/10203/83163
Appears in Collection
CS-Journal Papers(저널논문)
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