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Insignificant shadow detection for video segmentation

By D. Xu, J. Liu, Xuelong Li, Z. Liu and X. Tang

Abstract

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

Topics: csis
Publisher: The Institute of Electrical and Electronics Engineers
Year: 2005
OAI identifier: oai:eprints.bbk.ac.uk.oai2:450

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Citations

  1. (1986). A computational approach to edge detection,” doi
  2. (1997). A neural network approach to the elimination of road shadow for outdoor mobile robot,” in doi
  3. (1998). A noise robust method for 2-D shape estimation of moving objects in video sequences considering a moving camera,” doi
  4. (1992). A shadow handler in a video-based real-time traffic monitoring system,” in doi
  5. (1998). Automatic moving object and background separation,” doi
  6. (2002). Automatic segmentation of moving objects in video sequences: A region labeling approach,” doi
  7. (2002). C.KimandJ.N.Hwang,“Fastandautomaticvideoobjectsegmentation and tracking for content-based application,”
  8. (2002). Chen,“Efficientmoving objectsegmentation algorithm using background registration technique,”
  9. (1992). Computer and Robot Vision. doi
  10. (2003). Detecting moving objects, ghosts, and shadows in video streams,” doi
  11. (2003). Detecting moving shadows, algorithms, and evaluation,” doi
  12. (1999). Detection of moving cast shadows for object segmentation,” doi
  13. (2002). Efficient moving object segmentation algorithm using background registration technique,” doi
  14. (2002). Fast and automatic video object segmentation and tracking for content-based application,” doi
  15. (2000). I.Mikic,P.C.Cosman,G.T.Kogut,andM.M.Trivedi,“Movingshadow and object detection in traffic scenes,” in doi
  16. (2000). Moving shadow and object detection in traffic scenes,” in doi
  17. (1994). Seeded region growing,” doi
  18. (1998). Separation of moving objects and their shadows, and application to tracking of loci in the monitoring images,” in doi
  19. (2002). Shadow elimination for effective moving object detection with Gaussian models,” in doi
  20. (1992). Shadow identification,” in doi
  21. (2002). Shadowelimination for effective moving object detection with Gaussian models,” in doi
  22. (1997). Spatio-temporal video segmentation using a joint similarity measure,” doi
  23. (1998). Spatiotemporal segmentation based on region merging,” doi
  24. (1997). The MPEG-4 video standard verification model,” doi
  25. (2001). Toward detection of moving cast shadows for visual traffic surveillance,” in doi
  26. (1999). Video segmentation for content-based coding,” doi

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