IP Based Distributed Smart Camera Surveillance System for Forest Application

Kamal Lamichhane*
Department of Electronics and Communication, Nitte Meenakshi Institute of Technology, Yelahanka, Bangalore, India.
Periodicity:July - September'2013
DOI : https://doi.org/10.26634/jdp.1.3.2438

Abstract

Real time video surveillance is becoming increasingly important in the security of forest nowadays. Many efforts have been made in this field, to detect and track the human and human activities in scene and recognize simple motion such as walking and running. Real time Video surveillance is an alternative attempting to prevent the events to happen (or reduce their chances). This paper presents a digital real time video surveillance system with distributed IP-cameras. In this paper we present a real-time surveillance [3] system framework for recognizing complex activities in the defined area. In our system we detect moving objects in the scene [III] and use tracking algorithm [IV] to record activities for further analysis. Compared with the traditional surveillance system, an IP based distributed system surveillance offers much better flexibility in video content processing and transmission [5]. At the same time, it, also, can easily implement advanced features such as real time transmission of video and audio if connected through known ip address. Real time videos from distributed cameras are transmitted.

Keywords

Surveillance, Distributed IP-Cameras, Tracking Algorithm, Real Time Transmission

How to Cite this Article?

Lamichhane,K. (2013). IP Based Distributed Smart Camera Surveillance System For Forest Application. i-manager’s Journal on Digital Signal Processing, 1(3),14-16. https://doi.org/10.26634/jdp.1.3.2438

References

[1]. Remagnino, Jones, Paragios, and Regazzoni, (2002). Video Based Surveillance Systems, Computer Vision and Distributed Processing, Norwell, MA: Kluwer.
[2]. Blanz and Vetter, (2003). “Face recognition based on fitting morphable model,” IEEE PAMI, Vol. 25, No. 9, pp. 1063–1074.
[3]. R. T. Collins, A. J. Lipton, T. Canada, H. Fujiyoshi, D. Duggins, Y. Tsin, D. Tolliver, N. Enomoto, O. Hasegawa, P. Burt, and L.Wixson.(2000). A system for video surveillance and monitoring, Carnegie Mellon Univ., Pittsburgh, PA, Tech. Rep., CMU-RI-TR-00-12.
[4]. G. D. Hager, and P. N. Belhumeur, (1998). Efficient region tracking with parametric models of geometry and illumination, IEEE Trans. PAMI, Vol. 20, pp. 1025-1039
[5]. J.-G. Kim, H.S. Chang, J. Kim, and H.-M. Kim. (2004). Threshold-based camera motion characterization of MPEG video, ETRI Journal, 26(3):269{272.
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