Real Time Pedestrian Detection and Tracking for Driver Assistance Systems
Anjali Patil1, Arunkumar G.2
1Anjali Patil, M.Tech, Department of Computer Science and Engineering, VIT University, Vellore (Tamil Nadu), India.
2Arunkumar G, P.h.D, Assistant Professor, Department of Computer Science and Engineering, VIT University, Vellore (Tamil Nadu), India.
Manuscript received on 25 August 2019 | Revised Manuscript received on 01 September 2019 | Manuscript Published on 14 September 2019 | PP: 97-101 | Volume-8 Issue-5S3, July 2019 | Retrieval Number: E10250785S319/19©BEIESP | DOI: 10.35940/ijeat.E1025/0785S319
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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: In Autonomous driving technology detecting pedestrians and vehicles should be fast and efficient in order to avoid accidents. Pedestrian detection and tracking is challenging for complex real world scenes. In proposed system Kalman filter has been used to detect and track the pedestrians. From three frames initially eigen object is computed in video sequences for detection of moving objects, then shape information is used to classify humans and other objects. Moreover with the help of continues multiple frames occlusion between objects get calculated. In the proposed system an application is developed which gives automatic warning in case of doubtful activities performed by pedestrian of zone monitoring which can be used in various domains like defence and traffic monitoring. Proposed algorithm gives accurate moving object detection and advanced sensors are used to detect human movements ahead and alert the driver by using buzzer, result does not affect by body pose of individual.
Keywords: Pedestrian Detection, Tracking, ACF.
Scope of the Article: Multimedia and Real-Time Communication