Title :
Insignificant shadow detection for video segmentation
Author :
Xu, Dong ; Liu, Jianzhuang ; Li, Xuelong ; Liu, Zhengkai ; Tang, Xiaoou
Author_Institution :
Dept. of Electron. Eng. & Inf. Sci., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
To prevent moving cast shadows from being misunderstood as part of moving objects in change detection based video segmentation, this paper proposes a novel approach to the cast shadow detection based on the edge and region information in multiple frames. First, an initial change detection mask containing moving objects and cast shadows is obtained. Then a Canny edge map is generated. After that, the shadow region is detected and removed through multiframe integration, edge matching, and region growing. Finally, a post processing procedure is used to eliminate noise and tune the boundaries of the objects. Our approach can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance.
Keywords :
edge detection; image denoising; image matching; image segmentation; video signal processing; Canny edge map; edge matching; indoor environment; initial change detection mask; multiframe integration; noise elimination; shadow detection; video segmentation; Indoor environments; Layout; Light sources; MPEG 4 Standard; Monitoring; Object detection; Surveillance; Video coding; Videoconference; Working environment noise; Insignificant shadow detection; multiframe integration; region growing; video segmentation;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
DOI :
10.1109/TCSVT.2005.852402