Titlebook: Computational Visual Media; First International Shi-Min Hu,Ralph R. Martin Conference proceedings 2012 Springer-Verlag Berlin Heidelberg 2

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https://doi.org/10.1007/BFb0070306 related information hidden in different labels which is crucial for lots of applications, it is essential to extract a latent structure shared among different labels. This paper presents an incremental approach for extracting a shared subspace on dynamic dataset. With the incremental lossless matri

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Decomposition of the dirichlet form,logical research that line drawings trigger a neural response similar to natural color images, and propose a line-drawing-based 3D object recognition method. The contribution of the proposed method includes a feature defined for line drawings and a similarity metric for object recognition. Experimen

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Computational Visual Media978-3-642-34263-9Series ISSN 0302-9743 Series E-ISSN 1611-3349

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A Novel Customized Recompression Framework for Massive Internet Imagesto improve user experience and save costs as much as possible, a lot of internet applications always focus on how to achieve the appropriate image recompression. In this paper, we propose a novel framework to efficiently customize image recompression according to a variety of applications. And our n

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Intrinsic Image Decomposition with Local Smooth Assumption and Global Color Assumptionuse the problem is extremely ill-posed. Smooth assumption is widely used in many methods, but pixels in plain areas and in edge areas are not well distinguished. We improve this assumption by adding a weight to every pixel in the image so that the smoothness is measured accordingly. There are always