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

Dong Xu

Jianzhuang Liu

Senior Member

Xiaoou Tang

Xuelong Li

Zhengkai Liu

English

Xu, D.

Liu, J.

Li, Xuelong

Liu, Z.

Tang, X.

Birkbeck Institutional Research Online

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Insignificant shadow detection for video segmentation

Dong Xu, 

Jianzhuang Liu, 

Xuelong Li, 

Zhengkai Liu, 

Xiaoou Tang, 

Crossref

To prevent moving cast shadows from being misunderstood as part of moving objects in change detection based\ud
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\ud
map is generated. After that, the shadow region is detected and\ud
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\ud
can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance

Name not available

Abstract—To prevent moving cast shadows from being mis-understood 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 ap-proach can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance. Index Terms—Insignificant shadow detection, multiframe inte-gration, region growing, video segmentation. I

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http://mmlab.ie.cuhk.edu.hk/2005/01490560.pdf

Insignificant shadow detection for video segmentation

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