Video Object Detection and Segmentation Based on Proposal Boxes

摘要：

　　In this paper,we propose a new method to detect and segment foreground object in video automatically.Given a video sequence,our method begins by generating proposal bounding boxes in each frame,according to both static and motion cues.The boxes are used to detect the primary object in the sequence.We measure each box with its likelihood of containing a foreground object,connect boxes in adjacent frames and calculate the similarity between them.A layered Directed Acyclic Graph is constructed to select object box in each frame.With the help of the object boxes,we model the motion and appearance of the object.Motion cues and appearance cues are combined into an energy minimization framework to obtain the coherent foreground object segmentation in the whole video.Our method reports comparable results with stateof-the-art works on challenging benchmark dataset.

关键词： Video analysis Video object segmentation Object proposals

作者: Xiaodi Zhang Zhiguo Cao Yang Xiao Furong Zhao

作者单位: National Key Laboratory of Science and Technology on Multi-Spectral Information Processing,School of Automation,Huazhong University of Science and Technology,Wuhan,China

会议类型: 国际会议

会议名称: 第七届全国模式识别学术会议(The 7th Chinese Conference on Pattern Recognition,CCPR2016)

会议地点: 成都

会议语种:英文

页码: 304-317

在线出版日期: 2016-11-03（万方平台首次上网日期，不代表论文的发表时间）