TY - GEN
T1 - Human abnormal behavior detection based on RGBD video’s skeleton information entropy
AU - Bian, Ziyang
AU - Xu, Tingfa
AU - Su, Chang
AU - Luo, Xuan
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2016.
PY - 2016
Y1 - 2016
N2 - Conventional human abnormal behavior detection is mostly done in videos taken by visible-light cameras, and it is usually designed for a certain task. In order to solve the human abnormal behavior detection problem in general situation, this paper proposes a detection algorithm based on skeleton information entropy, by using the information from RGBD videos. In this paper, we assume that abnormal behavior is disordered. To sample the accurate features of human, we use RGBD cameras to get the skeleton information. Then, we analyze the information entropy of the angles of the skeleton, and find that the values of the information entropy are significantly higher in abnormal videos than in normal videos. The methods are tested in our database taken by Kinect in our lab and we present superior results whose recall is 92% and precision is 95.83%, and accuracy is 94%.
AB - Conventional human abnormal behavior detection is mostly done in videos taken by visible-light cameras, and it is usually designed for a certain task. In order to solve the human abnormal behavior detection problem in general situation, this paper proposes a detection algorithm based on skeleton information entropy, by using the information from RGBD videos. In this paper, we assume that abnormal behavior is disordered. To sample the accurate features of human, we use RGBD cameras to get the skeleton information. Then, we analyze the information entropy of the angles of the skeleton, and find that the values of the information entropy are significantly higher in abnormal videos than in normal videos. The methods are tested in our database taken by Kinect in our lab and we present superior results whose recall is 92% and precision is 95.83%, and accuracy is 94%.
KW - Human abnormal behavior detection
KW - Information entropy
KW - RGBD video
UR - http://www.scopus.com/inward/record.url?scp=84978286065&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-49831-6_74
DO - 10.1007/978-3-662-49831-6_74
M3 - Conference contribution
AN - SCOPUS:84978286065
SN - 9783662498293
T3 - Lecture Notes in Electrical Engineering
SP - 715
EP - 723
BT - Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems
A2 - Mu, Jiasong
A2 - Wang, Wei
A2 - Zhang, Baoju
A2 - Liang, Qilian
PB - Springer Verlag
T2 - 4th International Conference on Communications, Signal Processing, and Systems, CSPS 2015
Y2 - 23 October 2015 through 24 October 2015
ER -
