Spatiotemporal salient object detection by integrating with objectness

被引:6
|
作者
Wu, Tongbao [1 ,2 ]
Liu, Zhi [1 ,2 ]
Zhou, Xiaofei [1 ,2 ]
Li, Kai [1 ,2 ]
机构
[1] Shanghai Univ, Shanghai Inst Adv Commun & Data Sci, Shanghai 200444, Peoples R China
[2] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200444, Peoples R China
基金
中国国家自然科学基金;
关键词
Salient object detection; Saliency; Objectness; Object probability map; PARALLEL FRAMEWORK; DETECTION MODEL; VIDEO; IMAGE; SEGMENTATION; TREE;
D O I
10.1007/s11042-017-5334-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a novel spatiotemporal salient object detection method by integrating saliency and objectness, for videos with complicated motion and complex scenes. The initial salient object detection result is first built upon both saliency map and objectness map. Afterwards, the region size of salient object is adjusted to obtain the frame-wise salient object detection result by iteratively updating the object probability map, which is the combination of saliency map and objectness map. Finally, in order to enhance the temporal coherence, the sequence-level refinement is performed to generate the final salient object detection result. Experimental results on public benchmark datasets demonstrate that the proposed method consistently outperforms the state-of-the-art salient object detection methods.
引用
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页码:19481 / 19498
页数:18
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