Robust foreground object segmentation from handheld camera videos with occlusion map

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• 作者：Hao Xiong ; Zhiyong Wang ; Renjie He ; Dagan Feng
• 刊名：Multimedia Tools and Applications
• 出版年：2016
• 出版时间：May 2016
• 年：2016
• 卷：75
• 期：10
• 页码：5751-5776
• 全文大小：2,901 KB
• 刊物类别：Computer Science
• 刊物主题：Multimedia Information Systems
  Computer Communication Networks
  Data Structures, Cryptology and Information Theory
  Special Purpose and Application-Based Systems
  
• 出版者：Springer Netherlands
• ISSN：1573-7721
• 卷排序：75

文摘

Extracting foreground objects from videos captured by a handheld camera has emerged as a new challenge. While existing approaches aim to exploit several clues such as depth and motion to extract the foreground layer, there are limitations in handling partial movement and cast shadow. In this paper, we bring a novel perspective to address these two issues by utilizing occlusion map introduced by object and camera motion and taking the advantage of interactive image segmentation methods. For partial movement, we treat each video frame as an image and synthesize “seeding” user interactions (i.e., user manually marking foreground and background) with both forward and backward occlusion maps to leverage the advances in high quality interactive image segmentation. For cast shadow, we utilize a paired region based shadow detection method to further refine initial segmentation results by removing detected shadow regions. Experimental results from both qualitative evaluation and quantitative evaluation on the Hopkins dataset demonstrate both the effectiveness and the efficiency of our proposed approach.KeywordsVideo object segmentationOcclusion mapShadow removalHandheld camera