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Proceedings Paper

Interactive sketch animation by graph matching integrated with learning boundary detection
Author(s): Liangmei Hu; Henan Qu; Han Lv
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Paper Abstract

In this paper, we study an integrated framework to generate expressive sketch animation from real video with user interaction. It consists of two mainly steps: (i) image sketch computation by a learning-based edge detector; (ii) temporal sketch propagation by a robust stochastic matching algorithm. In the first step, given a video clip, the edge probability map on each frame is first computed by a discriminative model that is trained with a collection of various features. A template sketch is flexibly extracted from the beginning frame by threshold tuning, where user intervention is allowed to perfect the sketch template. Then this template is matched and localized to the following image sketches over frames by the graph-based matching algorithm. User interaction is allowed to sequentially correct the matching results. A number of sketch animations from real videos are presented to verify this framework in the experiments.

Paper Details

Date Published: 30 October 2009
PDF: 4 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74962T (30 October 2009); doi: 10.1117/12.833331
Show Author Affiliations
Liangmei Hu, Hefei Univ. of Technology (China)
Henan Qu, Hefei Univ. of Technology (China)
Han Lv, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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