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Notice of Retraction
Real-time human behavior recognition based on articulated model

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2 Author(s)
Weihua Wang ; Sch. of Comput. Sci. & Technol., Xidian Univ., Xian, China ; Zhijing Liu

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

In order to identify human behavior classification in Intelligent Security Monitoring System, an articulated model to extracting human body and classifying the behaviors of the moving objects is presented in this paper. An improved statistical Gaussian model is used as adaptive background updating method. After silhouettes of objects are extracted from the video images, we propose an articulated model of human, using the variety of body's trunk and limbs contour angles. The angles that can represent the pose of the skeleton model and length-width ratio of the human are used as feature vector. Finally Bayesian Networks is used for human posture training, modeling and activity matching to recognize the human motion. Experiment results have shown that this method gives stable performances and good robustness.

Published in:

Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on  (Volume:4 )

Date of Conference:

9-11 July 2010