Salient video object detection using a virtual border and guided filter

PATTERN RECOGNITION

卷:97

Article

Wang, Qiong^1,2  Zhang, Lu²  Zou, Wenbin³  Kpalma, Kidiyo² 

[1] Zhejiang Univ Technol, Coll Comp Sci & Technol, 288 Rd Liuhe, Hangzhou 310023, Zhejiang, Peoples R China

[2] Univ Rennes, INSA Rennes, CNRS, IETR,UMR 6164, F-35000 Rennes, France

[3] Shenzhen Univ, Shenzhen Key Lab Adv Machine Learning & Applicat, Guangdong Key Lab Intelligent Informat Proc, Coll Elect & Informat Engn, Shenzhen 518060, Peoples R China

关键词: Video salient object detection;    Distance transform;    Guided filter;    Global motion;   

DOI  :  10.1016/j.patcog.2019.106998

来源: Elsevier

【 摘 要 】

In this paper, we present a novel method for salient object detection in videos. Salient object detection methods based on background prior may miss salient region when the salient object touches the frame borders. To solve this problem, we propose to detect the whole salient object via the adjunction of virtual borders. A guided filter is then applied on the temporal output to integrate the spatial edge information for a better detection of the salient object edges. At last, a global spatio-temporal saliency map is obtained by combining the spatial saliency map and the temporal saliency map together according to the entropy. The proposed method is assessed on three popular datasets (Fukuchi, FBMS and VOS) and compared to several state-of-the-art methods. The experimental results show that the proposed approach outperforms the tested methods. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free