DocumentCode :
571640
Title :
An Adaptive Object Detection Scope Algorithm Based on SIFT
Author :
Lu, Yuanyuan ; Xu, Xiangyang ; Dai, Yaping ; Zheng, Bin
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
Volume :
2
fYear :
2012
fDate :
26-27 Aug. 2012
Firstpage :
100
Lastpage :
103
Abstract :
For camera movement causes moving objects detecting and tracking problems under complex background, we propose an adaptive object detection scope algorithm based on SIFT features. Firstly, let camera stationary and obtain three images to detect the moving object by using three-frame-difference method, then extract the object SIFT features. Secondly, according to the location and displacement of the object in the dynamic background, we determine the detection scope which matches the object well and obtain the minimum rectangle which can surround the right matching points in the detection scope, and then update the object template. The algorithm avoids the analysis of the complex relative motion between the object and the background, and reduces mismatch points and the calculation amount. This algorithm can quickly and accurately track the object without occlusion, and performs robust in small occlusion case.
Keywords :
difference equations; feature extraction; image matching; image sensors; object detection; object tracking; transforms; SIFT feature extraction; adaptive object detection scope algorithm; camera movement; matching points; mismatch point reduction; moving object detection problem; moving object tracking problem; object displacement; object location; object template; scale invariant feature transform; three-frame-difference method; Cameras; Equations; Feature extraction; Object detection; Search problems; Tracking; Vehicle dynamics; dynamic background; object tracking; three-frame-difference method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
Conference_Location :
Nanchang, Jiangxi
Print_ISBN :
978-1-4673-1902-7
Type :
conf
DOI :
10.1109/IHMSC.2012.120
Filename :
6305734
Link To Document :
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