AN EFFICIENT MOTION DETECTION AND CAPTURING SYSTEM FOR CCTV SURVEILLANCE

Sri Vasavi College, Erode Self-Finance Wing 3rd February 2017 National Conference on Computer and Communication NCCC’17

Format: Volume 5, Issue 1, No 7, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: P.DHINESH KUMAR,S.Anusuya

Reference:IJCS-189

View PDF Format

Abstract

Security and surveillance are important issues in today‟s world. Any behavior which is uncommon in occurrence and deviates from normally understood behavior can be termed as suspicious. This model aims at automatic detection of abnormal behavior in surveillance videos. We have targeted to create a system for the recognition of human activity and behavior, and extract new information of interest for end-users in highly secured indoor surveillance system. The objective of this project is to design a model for detection of abandoned objects and track abnormal human behaviors. The multi-object detection is done by background subtraction with the help of clustering techniques. Anomaly detection is done for tracking persons based on their individual appearance using Motion movement capture.

References

[1] Ahmed Taha, Hala H. Zayed, M. E. Khalifa and El-Sayed M. El-Horbaty, “On behavior analysis in video surveillance”, 6th International Conference on Information Technology, ICIT 2013. [2] Anwar. F., Petrounias. I., Morris, T., & Kodogiannis. V.,“Discovery of events with negative behavior against given sequential patterns”, In Fifth International IEEE conference on intelligent systems (IS „10). London, UK, 2010. [3] Anwar, F., & Petrounias, I., “Efficient Periodicity Mining of Sequential Patterns in a Post-Mining Environment”, In 4th International IEEE Conference “Intelligent Systems”,2008. [4] Badri Narayan Subudhi, Pradipta Kumar Nanda, Member, IEEE, and Ashish Ghosh, Member, IEEE, “A Change Information Based Fast Algorithm for Video Object Detection and Tracking”, IEEE transactions on circuits and systems for video technology , VOL. 21, NO. 7, July 2011. [5] Jinghua Wang and Guoyan Zhang, “Video Data Mining based on K-means Algorithm for Surveillance Video”, 2011 IEEE. [6] Jagannadan Varadarajan, Jean-Marc Odobez, R´emi Emonet “Multi-camera Open Space Human Activity Discovery for Anomaly Detection”, 8th IEEE International Conference on Advanced Video and Signal- Based Surveillance, 2011.


Keywords

Video Surveillance, Abnormal behaviour, Thresholding, Motion Detection.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.   

TOP
Facebook IconYouTube IconTwitter IconVisit Our Blog