Video Matting Using Multi-Frame Nonlocal Matting Laplacian

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We present an algorithm for extracting high quality temporally coherent alpha mattes of objects from a video. Our approach extends the conventional image matting approach, i.e. closed-form matting, to video by using multi-frame nonlocal matting Laplacian. Our multi-frame nonlocal matting Laplacian is dened over a nonlocal neighborhood in spatial temporal domain, and it solves the alpha mattes of several video frames all together simultaneously. To speed up computation and to reduce memory requirement for solving the multi-frame nonlocal matting Laplacian, we use the approximate nearest neighbor(ANN) to nd the nonlocal neighborhood and the k-d tree implementation to divide the nonlocal matting Laplacian into several smaller linear systems. Finally, we adopt the nonlocal mean regularization to enhance temporal coherence of the estimated alpha mattes and to correct alpha matte errors at low contrast regions. We demonstrate the eectiveness of our approach on various examples with qualitative comparisons to the results from previous matting algorithms.
Publisher
European Conference on Computer Vision Committee
Issue Date
2012-10
Language
English
Citation

12th European Conference on Computer Vision (ECCV 2012), pp.540 - 553

DOI
10.1007/978-3-642-33783-3_39
URI
http://hdl.handle.net/10203/172243
Appears in Collection
EE-Conference Papers(학술회의논문)
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