Optical Flow Based Object Movement Tracking
A. Balasundaram1, S. Ashok Kumar2, S. Magesh Kumar3
1A. Balasundaram*, Assistant Professor, Department of CSE, Saveetha School of Engineering, Chennai, India.
2S. Ashok Kumar, Assistant Professor, Department of CSE, Saveetha School of Engineering, Chennai, India.
3S. Magesh Kumar, Associate Professor, Department of CSE, Saveetha School of Engineering, Chennai, India.
Manuscript received on September 13, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 3913-3916 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1317109119/2019©BEIESP | DOI: 10.35940/ijeat.A1317.109119
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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: Object detection and tracking is one of the key tasks performed in video surveillance. The objects present in the area under surveillance is studied and analyzed with reference to the context. This plays a pivotal role in detecting and predicting anomalies based on the behavioral traits of objects observed under the surveillance region. Optical flow is one of the computer vision based approaches that is used for tracking the precise movement of objects. Several optical flow algorithms have been used to track and study the movement of objects. This work is motivated towards carrying out a thorough study different optical flow techniques and comparing the features of different optical flow approaches and implementing them for real time detection and tracking of objects in real time environment.
Keywords: Optical Flow, Object Detection, Object Tracking, Anomaly detection, Vision Based Object Tracking.