Tracking-based moving object detection

Shen, Hao, Li, Shuxiao, Zhang, Jinglan, & Chang, Hongxing (2013) Tracking-based moving object detection. In Proceedings of the 20th IEEE International Conference on Image Processing (ICIP 2013), IEEE, Melbourne, Australia, pp. 3093-3097.

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We present a novel approach for multi-object detection in aerial videos based on tracking. The proposed method mainly involves three steps. Firstly, the spatial-temporal saliency is employed to detect moving objects. Secondly, the detected objects are tracked by mean shift in the subsequent frames. Finally, the saliency results are fused with the weight map generated by tracking to get refined detection results, and in turn the modified detection results are used to update the tracking models. The proposed algorithm is evaluated on VIVID aerial videos, and the results show that our approach can reliably detect moving objects even in challenging situations. Meanwhile, the proposed method can process videos in real time, without the effect of time delay.

Impact and interest:

2 citations in Scopus
1 citations in Web of Science®
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ID Code: 69560
Item Type: Conference Paper
Refereed: Yes
Keywords: moving object detection, aerial video, tracking, real-time video processing, detection-by-tracking
DOI: 10.1109/ICIP.2013.6738637
ISBN: 9781479923410
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Copyright Statement: Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Deposited On: 31 Mar 2014 02:39
Last Modified: 26 Jun 2017 14:44

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