TY - GEN
T1 - A New Foreground Segmentation Method for Video Analysis in Different Color Spaces
AU - Shi, Hang
AU - Liu, Chengjun
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/26
Y1 - 2018/11/26
N2 - A new foreground segmentation method is presented in this paper for video analysis. Specifically, a new feature representation scheme is first proposed in different color spaces, namely, the RGB, the YIQ, and the YCbCr color spaces. The new feature vector, which integrates the color values in a particular color space, the horizontal and vertical Haar wavelet features, and the temporal difference features, enhances the discriminatory power. A new Global Foreground Modeling (GFM) method is then presented to improve upon the popular video analysis approaches. The Bayes classifier is finally applied for foreground segmentation in video. Experimental results using the New Jersey Department of Transportation (NJDOT) traffic video sequences show that the new foreground segmentation method achieves better performance than the popular video analysis methods.
AB - A new foreground segmentation method is presented in this paper for video analysis. Specifically, a new feature representation scheme is first proposed in different color spaces, namely, the RGB, the YIQ, and the YCbCr color spaces. The new feature vector, which integrates the color values in a particular color space, the horizontal and vertical Haar wavelet features, and the temporal difference features, enhances the discriminatory power. A new Global Foreground Modeling (GFM) method is then presented to improve upon the popular video analysis approaches. The Bayes classifier is finally applied for foreground segmentation in video. Experimental results using the New Jersey Department of Transportation (NJDOT) traffic video sequences show that the new foreground segmentation method achieves better performance than the popular video analysis methods.
UR - http://www.scopus.com/inward/record.url?scp=85059740599&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059740599&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2018.8545500
DO - 10.1109/ICPR.2018.8545500
M3 - Conference contribution
AN - SCOPUS:85059740599
T3 - Proceedings - International Conference on Pattern Recognition
SP - 2899
EP - 2904
BT - 2018 24th International Conference on Pattern Recognition, ICPR 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th International Conference on Pattern Recognition, ICPR 2018
Y2 - 20 August 2018 through 24 August 2018
ER -