Computer vision/Computer graphics collaboration techniques: - download pdf or read online

By André Gagalowicz, Wilfried Philips

ISBN-10: 3642018106

ISBN-13: 9783642018107

ISBN-10: 3642018114

ISBN-13: 9783642018114

This ebook constitutes the refereed lawsuits of the 4th overseas convention on computing device Vision/Computer photos Collaboration thoughts, MIRAGE 2009, held in Rocquencourt, France, in may well 2009. The forty-one revised complete papers provided have been rigorously reviewed and chosen from a complete of eighty three submissions. The papers conceal a variety of subject matters with specialize in desktop Vision/Computer pics collaboration ideas concerning snapshot analysis/synthesis methods particularly bearing on theoretical, computational, experimental or commercial facets of model-based photograph research and image-based version synthesis.

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Extra info for Computer vision/Computer graphics collaboration techniques: 4th International Conference, MIRAGE 2009, Rocquencourt, France, May 4-6, 2009: proceedings

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5 seconds. We found in our experiment that this time is sufficient to obtain an acceptable mesh quality (limited motion artifacts). Meshes, however, present various types of defects like holes, non manifold edges, bad shaped triangles and outliers, that should be corrected during the processing. The scanner also provides grayscale information. We do not use this information in our pipeline, but it may be extremely important to acquire, for example, 36 C. Lovato, U. Castellani, and A. Giachetti Fig.

ACM Computing Surveys 34(2), 211–262 (2002) 5. : Fuzzy Vector Median-Based Surface Smoothing. IEEE Trans. Visualization and Computer Graphics 10(3), 252–265 (2004) 6. : Mesh smoothing via mean and median filtering applied to face normals. In: Proc. Geometric Modeling and Processing - Theory and Applications, pp. 124–131 (2002) 7. : Bilateral mesh denoising. In: Proc. ACM SIGGRAPH, pp. 950–953 (2003) 8. : Non-iterative, feature preserving mesh smoothing. In: Proc. ACM SIGGRAPH, pp. 943–949 (2003) 9.

2 Mesh Segmentation Mesh points can be easily labelled according to the skeleton partitioning. We label the discretized space computing a distance map of the volume voxels from the final skeleton. Triangles of the mesh are then labelled according to the label of the voxel including its center. Being the space partitioning not depending on the mesh triangulation, the mesh labelling can be performed also on the processed mesh as well as on the original one. 3 Pose Estimation Human pose estimation can be achieved by finding the best fit an articulated stick figure over the acquired data.

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Computer vision/Computer graphics collaboration techniques: 4th International Conference, MIRAGE 2009, Rocquencourt, France, May 4-6, 2009: proceedings by André Gagalowicz, Wilfried Philips


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