@inproceedings{1c6604c5468a4955abf15aa5fa69d54b,
title = "An unsupervised video foreground co-localization and segmentation process by incorporating motion cues and frame features",
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.",
keywords = "Foreground Detection, Motion Boundaries, Object Co-Localization, Segmentation, Video Processing",
author = "Chao Zhang and Qian Zhang and Chi Zheng and Guoping Qiu",
note = "Publisher Copyright: {\textcopyright} 2018 SPIE.; 9th International Conference on Graphic and Image Processing, ICGIP 2017 ; Conference date: 14-10-2017 Through 16-10-2017",
year = "2018",
doi = "10.1117/12.2303460",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Hui Yu and Junyu Dong",
booktitle = "Ninth International Conference on Graphic and Image Processing, ICGIP 2017",
address = "United States",
}