Download Computational Visual Media: First International Conference, by Zhenhua Qu, Weiqi Luo, Jiwu Huang (auth.), Shi-Min Hu, Ralph PDF

By Zhenhua Qu, Weiqi Luo, Jiwu Huang (auth.), Shi-Min Hu, Ralph R. Martin (eds.)

This ebook constitutes the refereed complaints of CVM 2012, the 1st foreign convention on Computational visible Media, held in Beijing, China, in November 2012.
The 33 revised complete papers have been conscientiously reviewed and chosen from eighty one submissions. The papers are geared up in topical sections on photograph processing I and II, geometric processing, saliency, reputation, notion and studying, form research, media retrieval, and seize, rendering and visualization.

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Extra resources for Computational Visual Media: First International Conference, CVM 2012, Beijing, China, November 8-10, 2012. Proceedings

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5 Conclusion In this paper we proposed a novel algorithm to segment the image within the framework of evolutionary game theory. Our optimization method can efficiently solve energies with higher order clique to the problem of multi-label segmentation via PGG. Given an image and the corresponding segmentation cues, our algorithm is able to do the segmentation efficiently. We tested our approach on several challenging scenes. Both quantitative and qualitative experiments show that our algorithm outperforms the stateof-art.

IEEE (2007) 6 26. R. cn Abstract. This paper presents a novel method to simultaneously estimate the clothed and naked 3D shapes of a person. The method needs only a single photograph of a person wearing clothing. Firstly, we learn a deformable model of human clothed body shapes from a database. Then, given an input image, the deformable model is initialized with a few user-specified 2D joints and contours of the person. And the correspondence between 3D shape and 2D contours is established automatically.

When strategy update, player i learns to cooperate on layer k if the payoff is higher than that of the other layers. This new strategy is then used in the next round of the game. Eqn. 9 shows the updating rule of player i on layer l Sil (t + 1) = C πil (t) > πik (t), ∀k = l D otherwise (9) where πil (t) denotes the accumulate payoff at time step t, and Sil (t + 1) the strategy of player i on layer l in the next round. C, D are strategies of whether cooperate or defect. Finally, player i with strategy C is assigned label l.

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