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Author:

Li, Xiuzhi (Li, Xiuzhi.) | Xu, Chuanluo (Xu, Chuanluo.)

Indexed by:

CPCI-S

Abstract:

Moving object detection under a dynamic background has been a serious challenge in real-time computer vision applications. Global motion compensation approaches, a popular existing technique, aims at compensating the moving background for moving target segmentation. However, it suffers from inaccurate global motion parameters estimation. The paper presents a moving object detection technique that combines TV-L1 optical flow with SLIC superpixel segmentation to characterize moving objects from a dynamic background. SLIC superpixel segmentation can adhere to boundaries of objects, and thus improve the segmentation performance. TV-L1 optical flow implemented on GPU reports competitive smooth flow field with real-time performance. Experimental results on various challenging sequences demonstrate that the proposed approach achieve impressive performance.

Keyword:

Author Community:

  • [ 1 ] [Li, Xiuzhi]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China

Reprint Author's Address:

  • [Li, Xiuzhi]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China

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Source :

2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO)

Year: 2015

Page: 84-89

Language: English

Cited Count:

WoS CC Cited Count: 10

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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