Thu Dau Mot University Journal of Science

Entropy Measurement to Extract the Signification of Abnormal Activity from Camera’s Frames and its Application for Fall Detection

By Hoang Manh Ha, Tran Ba Minh Son, Nguyen Xuan Dung, Vo Quoc Thong
Published online 15/12/2020
DOI: 10.37550/tdmu.EJS/2020.04.081


Most of the indoor accidents are related with fall down. Many medical studies are point out that key factor for keeping patient’s life is fast response of monitoring system. In modern life, peoples are isolated with neighbor, especially in living quarters. Therefore many solutions are developed for falling down monitoring that base on wearable sensors. These methods require of an expensive sensors system with electric power supplier and telecommunication devices. In context of patients with disease and weak status, patients are trend to remove sensor system. This issue requires to find out another approach so that sensors system will not be needed. We study the fall detection by monitoring camera. For increase the accuracy, we proposed a simple and effective method to extract features of abnormal activities. By tracking the magnitude of entropy and its distribution, our fall detection model has a capability of differentiating falls from other activities

Full text

View PDF


[1]   Aggarwal.  J.K,  Ryoo.  M.S (2011),  Human  activity  analysis:  A  review.  ACM  Comput. Surv , 43,  art no. 16

[2]   Khalid,  S.  Naftel (2005),  A.  Classifying  spatiotemporal  object  trajectories  using  unsupervised  learning of  basis  function  coefficients.  In  Proceedings  of  the  3rd  ACM  International  Workshop  on  Video Surveillance & Sensor Networks, New York, NY, USA, 1–2, pp. 45–52.

[3]   Yin,  J.;  Meng,  Y (2009), Abnormal behavior recognition using self-adaptive hidden markov models. Lect. Notes Comput. Sci, 5627, 337–346.

[4]   Loy,  C.C.;  Xiang,  T.;  Gong,  S (2009), Surveillance video behaviour profiling and anomaly detection. Proc. SPIE, 7486, 74860E.

[5]   Hu,  D.H.;  Yang,  Q (2008), Concurrent and interleaving goal and activity recognition.  In Proceedings of the National Conference on Artificial Intelligence, Chicago, IL, USA, pp. 1363–1368

[6]   Lui, Y.; Beveridge, J.R.; Kirby, M (2010). Action classification on product manifolds. In Proceedings of IEEE  Computer  Society  Conference  on  Computer  Vision  and  Pattern  Recognition, San Francisco, CA, USA, pp. 833–839.

[7]   Lui,  Y (2012).  Advances in Matrix  Manifolds  for  Computer  Vision.  Image Vision Comput,  30, 380–388

[8]   Anice JahanjooMarjan Naderan and Mohammad Javad Rashti (2020), Detection and multi-class classification of falling in elderly people by deep belief network algorithms, Journal of Ambient Intelligence and Humanized Computing.

[9]    Shannon, Claude E (1948). A Mathematical Theory of Communication. Bell System Technical Journal27(3), 379–423.

[10]Teng Li, Huan Chang, Meng Wang, Bingbing Ni, Richang Hong, and Shuicheng Yan (2015), “Crowded Scene Analysis: A Survey”, IEEE Transactions on circuits and systems for video technology, 25(3)

[11]O. Popoola and K. Wang (2012), Video-based abnormal human be-havior recognition -a review Systems, Man, and Cybernet-ics, Part C: Applications and Reviews. IEEE Transactions on , 42(6), 865–878

[12]G. J. Burghouts, V. P. Slingerland, H. ten R.J.M, H. den R.J.M, and K. Schutte (2014), Complex threat detection: Learning vs. rules, using a hierarchy of features, in 11th IEEE International Conference on Advanced Video and Signal Based Surveil lance. IEEE, pp. 375–380.

[13]H. Nallaivarothayan, C. Fookes, S. Denman, and S. Sridharan (2014), An mrf  based  abnormal event detection approach using motion and appearance features, in 11th IEEE International Confer-ence on Advanced Video and Signal Based Surveil lance.  IEEE, pp. 343–348

[14]Y. Benabbas, N. Ihaddadene, and C. Djeraba (2011), Motion pattern extraction and event detection for automatic visual surveillance, Journal on Image and Video Processing, vol. 7, pp. 1–15.

[15]C. Piciarelli, C. Micheloni, and G. L. Foresti (2008), Trajectory-based anomalous event  detection. IEEE Trans. Circu its Syst. Video Techn. , 18(11), 1544–1554.

[16]B. Antic and B. Ommer (2011), Video parsing for abnormality detection. IEEE International Conference on Computer Vision, ICCV 2011, pp. 2415–2422.

[17]A. Adam, E. Rivlin, I. Shimshoni, and D. Reinitz (2008), Robust real-time unusual event detection using multiple fixed-location monitors. IEEE Transactions on Pattern Analysis and Machine Intel ligence, 30(3), 555–560.

[18]M. Roshtkhari and M. Levine (2013), Online dominant and anomalous behavior detection in videos, in Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, pp. 2611–2618.

[19]V. Mahadevan, W. Li, V. Bhalodia, and N. Vasconcelos (2010), Anomaly detection in crowded scenes, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1975–1981

Publication Information


Thu Dau Mot University, Viet Nam

Honorary Editor-in-Chief and Chairman of the Editorial Board

Assoc. Prof. Nguyen Van Hiep

Deputy Editor-in-Chief

PhD. Trần Hạnh Minh Phương
Thu Dau Mot University

Editorial Board

Prof. Tran Van Doan
Fujen University, Taiwan
Prof. Zafar Uddin Ahmed
Vietnam National University Ho Chi Minh City

Prof.Dr. Phillip G.Cerny
The University of Manchester, United Kingdom
Prof. Ngo Van Le
University of Social Sciences and Humanities (VNU-HCM)

Prof. Bui The Cuong
Southern Institute of Social Sciences​​​​​​​
Prof. Le Quang Tri
Can Tho University

Assoc. Prof. Nguyen Van Duc
Animal Husbandry Association of Vietnam
Assoc. Prof. Ted Yuchung Liu
National Pingtung University, Taiwan

PhD. Anita Doraisami
Economics Monash University, Australia
Prof. Dr. Andrew Seddon
Asia Pacific University of Technology & innovation (APU)

Assoc. Prof. Le Tuan Anh
Thu Dau Mot University
Prof. Abtar Darshan Singh
Asia Pacific University, Malaysia

Prof.Dr. Ron W.Edwards
The University of Melbourne, Australia
Assoc. Prof. Hoang Xuan Nien
Thu Dau Mot University

PhD. Nguyen Duc Nghia
Vietnam National University Ho Chi Minh City
PhD. Bao Dat
Monash University (Australia)

PhD. Raqib Chowdhury
Monash University (Australia)
PhD. Nguyen Hoang Tuan
Thu Dau Mot University

PhD. Nguyen Thi Lien Thuong
Thu Dau Mot University


Nguyen Thi Man
Thu Dau Mot University