Certain Approaches of Real Time Object Tracking in Video Sequences on Embedded Linux Platform
Namitha Mathew1, Prabhakar. S2, K. Gerard Joe Nigel3
1Namitha Mathew, M.Tech, PG Scholar, Department of Embedded Systems Electronics and Instrumentation Engineering, Karunya University, Coimbatore (Tamil Nadu), India.
2S.Prabakar, Assistant Professor, Department of Electronics and Instrumentation Engineering, Karunya University, Coimbatore (Tamil Nadu), India.
3K.Gerard Joe Nigel, Assistant Professor, Department of Electronics and Instrumentation Engineering, Karunya University, Coimbatore (Tamil Nadu), India.
Manuscript received on 12 March 2013 | Revised Manuscript received on 21 March 2013 | Manuscript Published on 30 March 2013 | PP: 102-105 | Volume-2 Issue-4, March 2013 | Retrieval Number: D0516032413/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Video tracking in real time is one of the most important topic in the field of computer Vision. Detection and tracking of moving objects in the video scenes is the first relevant step in the information extraction in many computer vision applications.This idea can be used for the surveillance purpose, video annotation, traffic monitoring and also in the field of medical In this paper, we are discussing about the different methods for the video trackingusing Python Opencv software and the implementation of the tracking system on the Beagleboard XM. Background Subtraction method, and color based contour tracking are the different methods using for the tracking.And finally, we concluded that the background subtraction method is most efficient method for tracking all the moving objects in the frames.
Keywords: Surveillance, Python Opencv, Background Subtraction Method, Contour Tracking.
Scope of the Article: Embedded Networks