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Static and Moving Object Detection Using Flux Tensor with Split Gaussian Models
AbstractIn this paper, we present a moving object detection system named Flux Tensor with Split Gaussian models (FTSG) that exploits the benefits of fusing a motion computation method based on spatio-temporal tensor formulation, a novel foreground and background modeling scheme, and a multi-cue appearance comparison. This hybrid system can handle challenges such as shadows, illumination changes, dynamic background, stopped and removed objects. Extensive testing performed on the CVPR 2014 Change Detection benchmark dataset shows that FTSG outperforms state-ofthe-art methods.
Related Material
[pdf][bibtex]@InProceedings{Wang_2014_CVPR_Workshops,
author = {Wang, Rui and Bunyak, Filiz and Seetharaman, Guna and Palaniappan, Kannappan},
title = {Static and Moving Object Detection Using Flux Tensor with Split Gaussian Models},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2014}
}
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