Moving Object Detection and Tracking Based on the Contour Extraction and Centroid Representation

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Author(s): Naveenkumar M (National Institute of Technology Trichy, India), Sriharsha K. V. (National Institute of Technology Trichy, India)and Vadivel A (National Institute of Technology Trichy, India)
Copyright: 2019
Pages: 11
Source title: Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7368-5.ch012

Keywords: Artificial Intelligence / Engineering Science Reference / Human-Computer Interaction / Social Sciences & Humanities

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Abstract

This chapter presents a novel approach for moving object detection and tracking based on contour extraction and centroid representation (CECR). Firstly, two consecutive frames are read from the video, and they are converted into grayscale. Next, the absolute difference is calculated between them and the result frame is converted into binary by applying gray threshold technique. The binary frame is segmented using contour extraction algorithm. The centroid representation is used for motion tracking. In the second stage of experiment, initially object is detected by using CECR and motion of each track is estimated by Kalman filter. Experimental results show that the proposed method can robustly detect and track the moving object.

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Moving Object Detection and Tracking Based on the Contour Extraction and Centroid Representation

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