Multi Target Tracking Access with Data Association in Distributed Camera Networks
Azmira Krishna1, CMAK Zeelan Basha2, Pradeep Raj Savarapu3, Soumya Ranjan Nayak4, S. Siva Kumar5
1Azmira Krishna, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
2CMAK Zeelan Basha, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
3Pradeep Raj Savarapu, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
4Soumya Ranjan Nayak, Chitkara University Institute of Engineering and Technology Chitkara University, (Punjab), India.
5S. Siva Kumar, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
Manuscript received on 11 October 2019 | Revised Manuscript received on 20 October 2019 | Manuscript Published on 02 November 2019 | PP: 412-417 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10630982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1063.0982S1119
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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: Data Association in Distributed Camera Network is a new method to analyse the large volume of video information in camera networking. It is an important step in multi camera multi target tracking. Distributed processing is a new paradigm to analyse the videos in camera network and each camera acts on its own and all cameras cooperatively work together to achieve a common goal, In this paper, we have addresses the problem of Distributed Data Association(DDA) to obtain the feet position of the object. These positions are shared with its immediate neighbours and find local matches using homography. By propagating these local matches across the network in order to obtain the global associations. In this proposed method DDA is less complex and improves the high accuracy compared to the centralized methods (STSPIE, EMTIC, JPDAEKCF, CSPIF, and CEIF).
Keywords: DDA, Networks, STSPIE, EMTIC, JPDAEKCF, CSPIF, CEIF.
Scope of the Article: Data Visualization