Robust vision-based multiple moving object detection and tracking from video sequences

Khalifa, Othman Omran and Abdul Malek, Norun and Ahmed, Kazi Istiaque and Abdul Rahman, Farah Diyana (2018) Robust vision-based multiple moving object detection and tracking from video sequences. Indonesian Journal of Electrical Engineering and Computer Science, 10 (2). pp. 817-826. ISSN 2502-4752

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Abstract

Detection of Moving Objects and Tracking is one of the most concerned issue and is being vastly used at home, business and modern applications. It is used to identify and track of an entity in a significant way. This paper illustrates the way to detect multiple objects using background subtraction methods and extract each object features by using Speed-Up Robust Feature algorithm and track the features through k-Nearest Neighbor processing from different surveillance videos sequentially. In the detection of object of each frame, pixel difference is calculated with respect to the reference background frame for the detection of an object which is only suitable for any ideal static condition with the consideration of lights from the environment. Thus, this method will detect the complete object and the extracted feature will be carried out for the tracking of the object in the multiple videos by one by one video. It is expected that this proposed method can commendably abolish the impact of the changing of lights.

Item Type:	Article (Journal)
Additional Information:	4119/62561
Uncontrolled Keywords:	Detection of moving object, Tracking, Reference background, SURF, KNN,
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Prof. Dr Othman O. Khalifa
Date Deposited:	28 Mar 2018 15:17
Last Modified:	09 Aug 2018 15:15
URI:	http://irep.iium.edu.my/id/eprint/62561

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