Moving Object Detection and Tracking under Different Occlusion Conditions in Video Sequences
Arjun Nelikanti1, G. Karuna2, G. Venkata Rami Reddy3
1Arjun Nelikanti, Research Scholar, Department of CSE, JNTUH, Hyd, India.
2Dr. G. Karuna, Professor, Department of CSE, GRIET, Hyderabad, India.
3Dr. G. Venkata Rami Reddy, Professor, Department of CSE, SIT, JNTUH, Hyderabad, India.
Manuscript received on 27 August 2019. | Revised Manuscript received on 01 September 2019. | Manuscript published on 30 September 2019. | PP: 2640-2647 | Volume-8 Issue-11, September 2019. | Retrieval Number: K19510981119/2019©BEIESP | DOI: 10.35940/ijitee.K1951.098111
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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: This paper proposed a novel method for the detection and tracking of hand-thrown object in a video sequence in real time sports events. This paper mainly aimed to detect regions of the object in a set of outdoor and indoor videos in different occlusion conditions, and used Kalman filter to detect object on different trajectories over a fixed time window. This approach proved that the thrown object is successfully detected in various cases under occlusion and non-occlusion conditions with different backgrounds. To evaluate the accuracy, two different types of performance evaluations metrics are used based on object detection and tracking. The results shows that significant performance, the average accuracy of the object detecting is 97.89% and tracking is 98.35%.
Keywords: Kalman Filter , Object detection, Object tracking, Occlusion.
Scope of the Article: Object detection