ICTACT Journal on Image and Video Processing

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Automated Human Detection and Tracking for Surveillance Applications


Affiliations
1 School of Computer Engineering and Technology, MIT Academy of Engineering, India
     

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Safeguarding a country’s border is very vital to its nation. A nation’s security is determined by the kind of security imposed at the border. Proper surveillance system needs to be imposed at border because of numerous reasons which include drug smuggling, illegal immigrants crossing the borders and last but not the least, terrorist intrusion. To protect our border from these activities we need to monitor, filter and detect if there is any motion or any kind of activity that might lead to intrusion in our borders. For this we need 247, surveillance and hence an automated surveillance system needs to be developed. The existing systems are not efficient enough to detect threats if the intruders are using some kind of camouflage or cover. To overcome these drawbacks of the existing systems we intend to use thermal imaging cameras. The focus is to use thermal imaging cameras to capture the images for detection and tracking of the human/object, so as to analyze and predict their behaviour and intentions. The use of thermal imaging unlike the optical camera will help the system to perform detection of suspects which are hidden behind an obstacle for e.g. a bush. The thermal imaging will perform the detection at night with the same efficiency as in the daytime. The surveillance system is designed in order to achieve the objective of safeguarding the border, thus satisfying the aim of detecting threats and minimizing false alarms.

Keywords

Image Processing, Thermal Imagers, Machine Learning, Border Surveillance, Neural Networks.
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  • Alok K. Singh Kushwaha, Chandra Mani Sharma, Manish Khare, Rajneesh Kumar Srivastava and Ashish Khare, “Automatic Multiple Human Detection and Tracking for Visual Surveillance System”, Proceedings of International Conference on Informatics, Electronics and Vision, pp. 12-19, 2012.

  • Neha Gabal, Neelam Barak and Shipra Aggarwal, “Motion Detection, Tracking and Classification for Automated Video Surveillance”, Proceedings of 1st IEEE International Conference on Power Electronics Intelligent Control and Energy Systems, pp. 1-5, 2016.

  • Chun-Ming Li, Yu-Shan Li, Shu-Hai Wang and Xiu-Qing Zhang, “Moving Human Body Detection in Video Sequences”, Proceedings of 6th International Conference on Machine Learning and Cybernetics, pp. 19-22, 2007.

  • Hyukmin Eum, Jeisung Lee, Changyong Yoon and Mignon Park, “Human Action Recognition for Night Vision using Temporal Templates with Infrared Thermal Camera”, Proceedings of 10th International Conference on Ubiquitous Robots and Ambient Intelligence, pp. 1-5, 2012.

  • Xiaoshi Zheng, Yanling Zhao, Na Li and Huimin Wu, “An Automatic Moving Object Detection Algorithm for Video Surveillance Applications”, Proceedings of International Conference on Embedded Software and Systems, pp. 21-27, 2009.

  • Amin Ullah, Jamil Ahmad, Khan Muhammad, Muhammad Sajjad and Sung Wook Baik, “Action Recognition in Video Sequences using Deep Bi-Directional LSTM With CNN Features”, IEEE Access, Vol. 6, pp. 1155-1166, 2017.

  • Christian Herdianto Setjo and Faridah Balza Achmad, “Thermal Image Human Detection using HAAR-Cascade Classifier”, Proceedings of International Annual Engineering Seminar, pp. 1-3, 2017.

  • Palwasha Afsar, Paulo Cortez and Henrique Santos, “Automatic Human Action Recognition from Video using Hidden Markov Model”, Proceedings of IEEE 18th International Conference on Computational Science and Engineering, pp. 21-23, 2015.

  • Shipra Ojha and Sachin Sakhare, “Image Processing Techniques for Object Tracking in Video Surveillance- A Survey”, Proceedings of IEEE International Conference on Pervasive Computing, pp. 1-5, 2015.

  • C.S. Sanoj, N. Vijayaraj and D. Rajalakshmi “Vision Approach Of Human Detection and Tracking using Focus Tracing Analysis”, Proceedings of IEEE International Conference on Information Communication and Embedded Systems, pp. 12-17, 2013.

  • Nizar Zarka, Ziad Alhalah and Rada Deeb, “Real-Time Human Motion Detection and Tracking”, Proceedings of International Conference on Information and Communication Technologies from Theory to Applications, pp. 1-6, 2008.


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  • Automated Human Detection and Tracking for Surveillance Applications

Abstract Views: 288  |  PDF Views: 0

Authors

Avaneesh Tripathi
School of Computer Engineering and Technology, MIT Academy of Engineering, India
Milind Pathak
School of Computer Engineering and Technology, MIT Academy of Engineering, India
Amritha Sharma
School of Computer Engineering and Technology, MIT Academy of Engineering, India
Parth Vijay
School of Computer Engineering and Technology, MIT Academy of Engineering, India
S. A. Jain
School of Computer Engineering and Technology, MIT Academy of Engineering, India

Abstract


Safeguarding a country’s border is very vital to its nation. A nation’s security is determined by the kind of security imposed at the border. Proper surveillance system needs to be imposed at border because of numerous reasons which include drug smuggling, illegal immigrants crossing the borders and last but not the least, terrorist intrusion. To protect our border from these activities we need to monitor, filter and detect if there is any motion or any kind of activity that might lead to intrusion in our borders. For this we need 247, surveillance and hence an automated surveillance system needs to be developed. The existing systems are not efficient enough to detect threats if the intruders are using some kind of camouflage or cover. To overcome these drawbacks of the existing systems we intend to use thermal imaging cameras. The focus is to use thermal imaging cameras to capture the images for detection and tracking of the human/object, so as to analyze and predict their behaviour and intentions. The use of thermal imaging unlike the optical camera will help the system to perform detection of suspects which are hidden behind an obstacle for e.g. a bush. The thermal imaging will perform the detection at night with the same efficiency as in the daytime. The surveillance system is designed in order to achieve the objective of safeguarding the border, thus satisfying the aim of detecting threats and minimizing false alarms.

Keywords


Image Processing, Thermal Imagers, Machine Learning, Border Surveillance, Neural Networks.

References