DocumentCode
457161
Title
Adaptive Step Size Window Matching for Detection
Author
Mekuz, Nathan ; Derpanis, Konstantinos G. ; Tsotsos, John K.
Author_Institution
Dept. of Comput. Sci. & Center for Vision Res., York Univ., Toronto, Ont.
Volume
2
fYear
0
fDate
0-0 0
Firstpage
259
Lastpage
262
Abstract
An often overlooked problem in matching lies in selecting an appropriate step size. The selection of the step size for real-time applications is critical both from the point of view of computational efficiency and detection performance. Current systems set the step size in an ad hoc manner. This paper describes an algorithm for selecting the step size based on a theoretical worst case analysis. We have implemented this adaptive step size method in an object detection algorithm. Experimental evaluation demonstrates the effectiveness of our proposed algorithm
Keywords
image matching; object detection; adaptive step size window matching; object detection; step size selection; theoretical worst case analysis; Algorithm design and analysis; Application software; Computational efficiency; Computer science; Computer vision; Image reconstruction; Object detection; Optical devices; Stereo image processing; Stereo vision;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.224
Filename
1699196
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