Robust region-based background subtraction and shadow removing using color and gradient information

@article{Izadi2008RobustRB,
  title={Robust region-based background subtraction and shadow removing using color and gradient information},
  author={Mohammad Izadi and Parvaneh Saeedi},
  journal={2008 19th International Conference on Pattern Recognition},
  year={2008},
  pages={1-5}
}
In this paper, a novel algorithm for foreground detection and shadow removal is presented. The proposed method employs a region-based approach by processing two foregrounds resulted from gradient-and color-based background subtraction methods. The performance of the system is compared against conventional approaches for five indoor and outdoor video sequences. Experimental results confirm that the detection rate exceeds 90%, and the robustness is greatly improved. 
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References

Publications referenced by this paper.
Showing 1-10 of 15 references

Recursive unsupervised learning of finite mixture models

IEEE Transactions on Pattern Analysis and Machine Intelligence • 2004
View 4 Excerpts
Highly Influenced

Tracking Groups of People

Computer Vision and Image Understanding • 2000
View 6 Excerpts
Highly Influenced

Bez , “ A practical adaptive approach for dynamic background subtraction using an invariant colour model and object tracking

R. Mech Stauder, J. Ostermann
Pattern Recognition Letters • 2005

, M . Piccardi , and A . Prati , “ Detecting moving objects , ghosts , and shadows in video streams

R. Duraiswami Elgammal, D. Harwood, L. Davis
IEEE Trans . PAMI • 2003

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