Anomaly Detection in Surveillance Video Using Pose Estimation

  • K.V. Prema
  • A Thyagarajamurthy
Keywords: Bounding box,frame,keypoint


Anomalous events are generally infrequent, sparse,and unpredictable. Detection of people and continuously monitoring them and base on the human activity detecting anomaly event is challenging task. In this paper, we focus on keypoints detection of a person. We judge the abnormal behavior of the person by detecting the motion of key-points of that person. In the starting frame we select a bounding box. If some number of key-points are moved out of the bounding box then system gives an alert message.


[1] Yiran Xue, ,Peng Liu, Ye Tao, Xianglong Tang, “Abnormal Prediction Of Dense Crowd Videos By A Purpose Driven Lattice Boltzmann Model”,Int. J Math Comput. Sci. 2017 , Vol. 27, No. 1, pp. 181-194, February2017
[2] Meina Qiao, Tian Wang, Jiakun Li1, Ce Li, Zhiwei Lin, Hichem Snoussi,
[3] “Abnormal Event Detection based on Auto encoder fusing opticalflow ,Proceedings of the 36th Chinese Control Conference”, July2017.
[4] Dinesh Singh, C. Krishna Mohan, “Graph formulation of video activities for abnormal activity recognition”, Visual Learning and Intelligence Group (VIGIL), ScienceDirect, Pattern recognition, vol. 65, pp. 265-272, January 2017
[5] Peng Liu, Ye Tao, Wei Zhao, Xianglong Tang, “Abnormal crowd motion detection using double sparse representation”,Pattern Recognition Research enter,Neurocomputing, Vol. 269, pp. 3-12, June2017
[6] Kaelon Lloyd, Paul L. Rosin, David Marshall, Simon C. Moore, “Detecting violent and abnormal crowd activity using temporal analysis of Grey level co-occurrence matrix (GLCM)-based texture measures”, Machine Vision and Applications, Vol. 28. ,pp. 361-371, March2017
[7] Dongping Zhang, Kaihang Xu, Huailiang Peng, Ye Shen. “Abnormal Crowd Motion Behaviour Detection based on SIFT Flow”, International Journal of signal processing and pattern recognition”, Vol. 9, No. 1, pp. 289- 302, September2016
[8] Yu Zhao, Lei Zhou, Keren Fu, Jie Yang, “Abnormal Event Detection Using Spatio-Temporal Feature And NonnegativeLocality-
Constrained Linear Coding”, IEEE Conference, Vol. 9, pp. 3354-3358, June 2016
[9] Chein-I Chang, Yulei Wang,and Shih-Yu Chen, “Anomaly Detection Using Causal Sliding Windows”, IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, Vol. 7, pp. 3260- 3270, July2015
[10] Chunyu Chen, Yu Shao, and Xiaojun Bi,“Detection of Anomalous Crowd BehaviorBasedontheAccelerationFeature”,IEEESensorsJournal,Vol.15,
No. 12, pp. 7252-7261, December 2015
[11] jabez Ja, Dr.B.Muthukumar, “Intrusion Detection System (IDS): Anomaly Detection using Outlier Detection Approach”, International Conference on Intelligent Computing, Communication and Convergence(ICCC-2015), ScienceDirect, Vol. 48, pp. 338-346, April2015
[12] Miaomiao Ding, Jiahui Zhao, Fangyu Hu, “Abnormal Behavior Analysis Based on Examination Surveillance Video”, 9th International Symposium on Computational Intelligence and Design, Vol 16, pp. 2473-3547, June2016
[13] Luis Patino and James Ferryman University of Reading, “Abnormal behaviour detection on queue analysis from stereo cameras”, Computational Vision Group White knights, Vol 3, pp. 345-350, July2015
[14] Mark Marsden Kevin McGuinness Suzanne Little Noel E. OConnor, “Holistic features for real-time crowd behaviour anomaly detection”, IEEE conference, Vol. 9 , pp. 918-922, June2016
[15] Shangnan Liu, Qiang Cheng, Zhenjiang Zhu, Hao Zhang, “Analysis and Design of Public Places Crowd Stampede Early-Warning Simulating System”,International Conference on industrial Informatics, Vol 978-1-5990- 3575-5, pp. 210-213, May2016
[16] Ben-Syuan Huang, Shih-Chung Hsu and Chung-Lin Huang, “Abnormal behavior detection using conditional random fields”,Vol 8, pp.235-240, January 2016
[17] Real-time human gesture grading based on OpenPose, Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017 10th International Congress, 14-16 Oct. 2017, 10.1109/CISP- BMEI.2017.8301910
How to Cite
Prema, K., & Thyagarajamurthy, A. (2019). Anomaly Detection in Surveillance Video Using Pose Estimation. Asian Journal For Convergence In Technology (AJCT), 5(2). Retrieved from