TY - GEN
T1 - A novel spatio-temporal video object segmentation algorithm
AU - Zhu, Shiping
AU - Xia, Xi
AU - Zhang, Qingrong
AU - Belloulata, Kamel
PY - 2008
Y1 - 2008
N2 - Video object segmentation is a key technology in video processing, which is the foundation of the newly object-based video compression standard MPEG-4. A novel spatio-temporal video object segmentation algorithm is proposed in this paper, which is very efficient to acquire the video object moving in a static background. Firstly, video sequence is segmented with change detection algorithm to get segmentation result in temporal domain; Secondly, the spatial segmentation result is obtained by a segmentation algorithm based on local thresholds, which means each pixel in the image has its own threshold. In this algorithm, the threshold of a pixel in an image is estimated by calculating the mean of the grayscale values of its neighbor pixels, and the square variance of the grayscale values of the neighbor pixels is also calculated as an additional judge condition; Thirdly, the video object is extracted by spatio-temporal integration video segmentation algorithm. The experimental results show that the proposed spatio-temporal integration video object segmentation algorithm can extract the moving object in a video sequence with a static background accurately and efficiently.
AB - Video object segmentation is a key technology in video processing, which is the foundation of the newly object-based video compression standard MPEG-4. A novel spatio-temporal video object segmentation algorithm is proposed in this paper, which is very efficient to acquire the video object moving in a static background. Firstly, video sequence is segmented with change detection algorithm to get segmentation result in temporal domain; Secondly, the spatial segmentation result is obtained by a segmentation algorithm based on local thresholds, which means each pixel in the image has its own threshold. In this algorithm, the threshold of a pixel in an image is estimated by calculating the mean of the grayscale values of its neighbor pixels, and the square variance of the grayscale values of the neighbor pixels is also calculated as an additional judge condition; Thirdly, the video object is extracted by spatio-temporal integration video segmentation algorithm. The experimental results show that the proposed spatio-temporal integration video object segmentation algorithm can extract the moving object in a video sequence with a static background accurately and efficiently.
KW - Change detection
KW - Image segmentation
KW - Spatio-temporal integration
KW - Video object segmentation
UR - https://www.scopus.com/pages/publications/54549096034
U2 - 10.1109/ICIT.2008.4608672
DO - 10.1109/ICIT.2008.4608672
M3 - 会议稿件
AN - SCOPUS:54549096034
SN - 9781424417063
T3 - Proceedings of the IEEE International Conference on Industrial Technology
BT - 2008 IEEE International Conference on Industrial Technology, IEEE ICIT 2008 - Conference Proceedings
T2 - 2008 IEEE International Conference on Industrial Technology, IEEE ICIT 2008
Y2 - 21 April 2008 through 24 April 2008
ER -