Automatic moving object segmentation with accurate boundaries

Authors:
Jia Wang;Haifeng Wang;Qingshan Liu;Hanqing Lu
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Year:
2006

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Abstract

This paper presents a layer-model based method to segment moving objects from image sequence with accurate boundaries. The segmentation framework involves three stages: Motion seed detection, Motion layer expansion and Motion boundary refinement. In the first stage, motion seeds, which determine the amount and initial position of motion layers, are detected by corner matching between consecutive frames, and classified by global motion analysis. In the second stage, the detected motion seeds are expanded into motion layers. To preserve the spatial continuity, an energy function is defined to evaluate the spatial smoothness and accuracy of the layers. Then, Graph Cuts technique is used to solve the energy minimization problem and extract motion layers. In the last stage, the extracted layers are combined with edge information to find accurate boundaries of moving objects. The proposed method is tested on several image sequences and the experimental results illustrate its promising performance.