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Motion Cue Based Instance-level Moving Object Detection
Huang,Junjie1,2; Zou,Wei1,2; Zhu,Zheng1,2; Zhu,Jiagang1,2
Conference Name第31届中国控制与决策会议(2019CCDC)
Conference Date2019年6月3日-5日
Conference Place中国南昌

This paper studies the moving object detection, i.e., analyzing the amount, position and size of the moving objects in instance-level, which is meaningful for many computer vision problems. However, the existing methods are still not satisfying in accuracy, portability and speed. In this paper, we propose a novel framework which detects moving objects by analysis the consistency of the moving foreground. Instead of directly performing cluster algorithms on the moving foregound, we take two stages: analyzing the composition according to the local density of the moving foreground points and locating the targets by regressing some anchors. In this way, the proposed method doesn’t need any training processes and can be efficiently performed to detect moving objects with arbitrary classes. Besides, we create our own publicly available dataset PDMOD with sufficient data, general challenges and convictive evaluation protocols to fill the scarcity of the evaluational datasets.

Indexed ByEI
Document Type会议论文
Corresponding AuthorHuang,Junjie
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Huang,Junjie,Zou,Wei,Zhu,Zheng,et al. Motion Cue Based Instance-level Moving Object Detection[C],2019.
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