DocumentCode :
183029
Title :
A robust object detection algorithm based on background difference and LK optical flow
Author :
Guang Han ; Xiaofei Li ; Ning Sun ; Jixin Liu
Author_Institution :
Eng. Res. Center of Wideband Wireless Commun. Tech., Nanjing Univ. of Posts & Telecommun., Nanjing, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
554
Lastpage :
559
Abstract :
A robust object detection algorithm based on background difference and LK (Lucas-Kanade, LK) optical flow is proposed. Firstly the object detection algorithms based on background difference and LK optical flow are improved respectively, and then these two algorithms are effectively fused with a novel fusion method, the problems caused by using single algorithm in practical application are solved. The experimental results show that the proposed fusion algorithm can effectively make up for the defects of using single algorithm, the performance of the moving object detection under complex scene is better than the other algorithms, the results show that the proposed algorithm is a robust and accurate object detection method.1.
Keywords :
feature extraction; image fusion; image motion analysis; image sequences; object detection; LK optical flow; Lucas-Kanade optical flow; background difference; moving object detection; object detection method; robust object detection algorithm; Adaptive optics; Computer vision; Image motion analysis; Object detection; Object tracking; Optical imaging; Optical sensors; LK optical flow; SURF corner extraction; background difference; corner selection; object detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5147-5
Type :
conf
DOI :
10.1109/FSKD.2014.6980894
Filename :
6980894
Link To Document :
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