DocumentCode
1956073
Title
Notice of Retraction
Real-time human behavior recognition based on articulated model
Author
Weihua Wang ; Zhijing Liu
Author_Institution
Sch. of Comput. Sci. & Technol., Xidian Univ., Xian, China
Volume
4
fYear
2010
fDate
9-11 July 2010
Firstpage
254
Lastpage
258
Abstract
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.
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.
Keywords
Bayes methods; Gaussian processes; feature extraction; image recognition; statistical analysis; Bayesian network; activity matching; adaptive background updating method; articulated model; feature vector; human behavior classification; human posture modeling; human posture training; intelligent security monitoring system; real-time human behavior recognition; statistical Gaussian model; Face; Legged locomotion; Bayesian Networks; articulated model; contour angles; silhouettes;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564934
Filename
5564934
Link To Document