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Video Object Segmentation with Shadow Removal

S. Neelaveni

Abstract


Video segmentation is a key step in image sequence analysis and its results are extensively used for determining motion features of scene objects, as well as for compression. To overcome the problems of semiautomatic segmentation, it is necessary to develop an automatic segmentation algorithm that requires fast implementation without user assistance. These requirements are particularly important for real time applications. In this paper, moving segmentation algorithm using change detection based on background registration technique for video sequences is implemented. A background registration technique is used to construct constant background information from the video sequence. Gradient filter is used for shadow removal. Finally, a post-processing step is used to remove noise regions and produce a smooth shape boundary. Experimental results demonstrate that the proposed method can eliminate the noise region and thus achieves a significantly improved segmentation result. This algorithm makes use of the temporal information to achieve higher efficiency for video surveillance systems.

Keywords


Background Registration, Change Detection, Shadow Removal, Video Object Segmentation.

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References


T. Sikora, “The MPEG-4 video standard verification model,” IEEE Trans. Circuits Syst. Video Technol., vol. 7, pp. 19–31, Feb. 1997.

T. Meier and K. N. Ngan, “Automatic segmentation of moving objects for video object plane generation,” IEEE Trans. Circuits Syst. Video Technol., vol. 8, no. 7, pp. 525–538, Sep. 1998.

Robust Object Segmentation Using Adaptive Thresholding. Xiaxi Huang and Nikolaos V. Boulgouris. Department of electronic engineering king’s college London United Kingdom.

Robust Moving Objects Segmentation by Background Subtraction P. Spagnolo, M. Leo, T. D’Orazio, A. Distante Istituto di Studi sui Sistemi Intelligenti per l’Automazione - C.N.R. Via Amendola 166/5, 70126 Bari, ITALY.

A Robust Background Subtraction and Shadow Detection Thanarat Horprasert David Harwood Larry S. Davis Computer Vision.

Robust Foreground Segmentation from Color Video Sequences Using Background Subtraction with Multiple Thresholds, Hansung Kim†, Ryuuki Sakamoto†, Itaru Kitahara†‡, Tomoji Toriyama†, and Kiyoshi Kogure† Knowledge Science Lab, ATR, Keihanna Science City, Kyoto, 619-0288.

S. Y. Chien, S. Y. Ma, and L. G. Chen, “Efficient moving object segmentation algorithm using background registration technique,” IEEE Trans. Circuits Syst. Video Technol., vol. 12, no. 7, pp. 577–586, Jul. 2002.

Aach, A. Kaup, and R. Mester, “Statistical model-based change detection in moving video,” Signal Processing, vol. 31, pp. 165–180, Mar. 1993.

R. Mech and M. Wollborn, “A noise robust method for 2D shape estimation of moving objects in video sequences considering a moving camera,” Signal Processing, vol. 66, pp. 203–217, Apr. 1998.


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