DocumentCode :
2501605
Title :
Statistical Background Modeling: An Edge Segment Based Moving Object Detection Approach
Author :
Murshed, Manzur ; Ramirez, Adrian ; Chae, Oksam
Author_Institution :
Dept. of Comput. Eng., Kyung Hee Univ., Yongin, South Korea
fYear :
2010
fDate :
Aug. 29 2010-Sept. 1 2010
Firstpage :
300
Lastpage :
306
Abstract :
We propose an edge segment based statistical background modeling algorithm and a moving edge detection framework for the detection of moving objects. We analyze the performance of the proposed segment based statistical background model with traditional pixel based, edge pixel based and edge segment based approaches. Existing edge based moving object detection algorithms fetches difficulty due to the change in background motion, object shape, illumination variation and noise. The proposed algorithm makes efficient use of statistical background model using the edge-segment structure. Experiments with natural image sequences show that our method can detect moving objects efficiently under the above mentioned environments.
Keywords :
edge detection; image motion analysis; image segmentation; object detection; statistical analysis; background motion; edge segmentation; illumination variation; moving object detection; object shape; statistical background modeling algorithm; Image edge detection; Image segmentation; Lighting; Motion segmentation; Noise; Pixel; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Video and Signal Based Surveillance (AVSS), 2010 Seventh IEEE International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-8310-5
Type :
conf
DOI :
10.1109/AVSS.2010.18
Filename :
5597126
Link To Document :
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