A Review on Multiple Object Detection and Tracking in Smart City Video Analytics
Fancy Joy1, V. Vijaya kumar2
1Fancy Joy, Department of Computer Science, Sri Ramakrishna College of Arts and Science, Coimbatore (TamilNadu), India.
2Dr. V. Vijaya Kumar, Department of Computer Science, Sri Ramakrishna College of Arts and Science, Coimbatore (TamilNadu), India.
Manuscript received on 10 December 2018 | Revised Manuscript received on 17 December 2018 | Manuscript Published on 26 December 2018 | PP: 428-432 | Volume-8 Issue- 2S2 December 2018 | Retrieval Number: ES2132017519/19©BEIESP
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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: Moving object detection and tracking are the two important challenging tasks in the smart city video analytics system. It is challenging due to occlusion, presence of shadows, cluttering, dynamic background, noise etc. Detection of moving objects, tracking, object matching across multi-camera, and re-identification are the basic steps of multi camera video analytics system. Multiple object detection and tracking in smart city video analytics can be developed according to appropriateness of society such as intelligent surveillance, smart parking, traffic monitoring, vehicle navigation, smart healthcare etc. The goal of this paper is to analyze and review various approaches towards multiple object tracking.
Keywords: Object Detection, Object Tracking, Video Analytics, Multi Camera Surveillance.
Scope of the Article: Computer Science and Its Applications