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Hierarchical frame structure based interactive video object cutout

Published: 11 December 2011 Publication History

Abstract

Video object cutout aims to extract homogenous objects from background in a video clip, which is a key process in many video processing fields, such as video compositing, video stylized rendering and so on. In this paper, we present a novel video cutout method by matching hierarchical structure of video frames. We first segment each frame by mean shift and construct hierarchical structure as a tree in preprocess stage. We then require user's interaction to label objects in a key frame. We further model video segmentation as matching hierarchical structure of frame and proposed an inter-frame matching algorithm. Experimental results show that our method can achieve desirable video segmentation results.

References

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Bai, X., Wang, J., Simons, D., and Sapiro, G. 2009. Video snapcut: Robust video object cutout using localized claasifiers. ACM Transactions on Graphics 28, 3 (July), 243--248.
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Chuang, Y., Agarwala, A., Curless, B., Salesin, D., and Szeliski, R. 2002. Video matting of complex scenes. ACM Transactions on Graphics 21, 3 (July), 243--248.
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Collomosse, J., Rowntree, D., and Hall, P. 2005. Stroke surfaces: Temporally coherent artistic animations from video. IEEE Transactions on Visualiztion and Computer Graphics 11, 4 (July/August), 540--549.
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Comaniciu, D., and Meer, P. 2002. Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 5 (May), 603--619.
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Comaniciu, D. 2002. Image segmentation using clustering with saddle point detection. In Proceedings of International Conference on Image Processing, ICIP.
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DeMenthon, D. 2002. Spatio-temporal segmentation of video by hierarchical mean shift analysis. In Proceedings of the Statistical Methods in Video Processing Workshop, Monash Univ. Copenhagen, Denmark.
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Li, Y., Sun, J., and Shum, H. 2005. Video object cut and paste. ACM Transactions on Graphics 24, 3 (July), 595--600.
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Paris, S., and Durand, F. 2007. A topological approach to hierarchical segmentation using mean shift. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE, 1978--1985.
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Wang, J., Bhat, P., Colburn, R., Agrawala, M., and Cohen, M. 2005. Interactive video cutout. ACM Transactions on Graphics 24, 3 (July), 585--594.

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cover image ACM Conferences
VRCAI '11: Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
December 2011
617 pages
ISBN:9781450310604
DOI:10.1145/2087756
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 December 2011

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Author Tags

  1. frame matching
  2. hierarchical mean shift
  3. video object cutout
  4. video segmentation

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Overall Acceptance Rate 51 of 107 submissions, 48%

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