An unsupervised video foreground co-localization and segmentation process by incorporating motion cues and frame features

Chao Zhang; Qian Zhang; Chi Zheng; Guoping Qiu

doi:10.1117/12.2303460

10 April 2018 An unsupervised video foreground co-localization and segmentation process by incorporating motion cues and frame features

Chao Zhang, Qian Zhang, Chi Zheng, Guoping Qiu

Author Affiliations +

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061529 (2018) https://doi.org/10.1117/12.2303460
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

Video foreground segmentation is one of the key problems in video processing. In this paper, we proposed a novel and fully unsupervised approach for foreground object co-localization and segmentation of unconstrained videos. We firstly compute both the actual edges and motion boundaries of the video frames, and then align them by their HOG feature maps. Then, by filling the occlusions generated by the aligned edges, we obtained more precise masks about the foreground object. Such motion-based masks could be derived as the motion-based likelihood. Moreover, the color-base likelihood is adopted for the segmentation process. Experimental Results show that our approach outperforms most of the State-of-the-art algorithms.

Citation Download Citation

Chao Zhang, Qian Zhang, Chi Zheng, and Guoping Qiu "An unsupervised video foreground co-localization and segmentation process by incorporating motion cues and frame features", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061529 (10 April 2018); https://doi.org/10.1117/12.2303460

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available