Video Salient Object Detection Based on Group Sparsity

摘要：

　　In this paper,we present a novel video salient object detection method based on group sparsity.Specially,both temporal and spatial saliency detection are considered.First,the temporal and spatial dictionaries are firstly constructed separately based on the appearance model and the motion feature contrast of each frame.Then the temporal saliency detection of each frame can be reduced to the sparse reconstruction problem based on the temporal dictionary to generate the temporal saliency map.A similar sparse reconstruction process is adopted to generate the spatial saliency map.Finally,the temporal saliency map and spatial saliency map are combined adaptively to generate the final spatiotemporal saliency map.Several experiments show that the proposed algorithm can detect salient objects accurately under scenes with large salient objects or dynamic backgrounds compared with the existing methods.

关键词： Salient object detection Spatiotemporal saliency detection Group sparsity Appearance model

作者: PAN Yunhui LIANG Ning ZHANG Qiang LIU Yi

作者单位: Center for Complex Systems,School of Mechano-electronic Engineering,Xidian University,Xi”an,China

会议类型: 国内会议

会议名称: 2017中国智能物联系统会议

会议地点: 厦门

会议语种:英文

页码: 159-166

在线出版日期: 2017-11-17（万方平台首次上网日期，不代表论文的发表时间）