By André Gagalowicz, Wilfried Philips
This publication constitutes the refereed lawsuits of the 4th foreign convention on computing device Vision/Computer pictures Collaboration ideas, MIRAGE 2009, held in Rocquencourt, France, in could 2009. The forty-one revised complete papers provided have been conscientiously reviewed and chosen from a complete of eighty three submissions. The papers disguise a variety of themes with specialise in machine Vision/Computer pictures collaboration options regarding photograph analysis/synthesis techniques specifically referring to theoretical, computational, experimental or business features of model-based photograph research and image-based version synthesis.
Read or Download Computer vision/Computer graphics collaboration techniques: 4th International Conference, MIRAGE 2009, Rocquencourt, France, May 4-6, 2009: proceedings PDF
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Additional info for Computer vision/Computer graphics collaboration techniques: 4th International Conference, MIRAGE 2009, Rocquencourt, France, May 4-6, 2009: proceedings
An interesting aspect of the procedure proposed is that it can be performed iteratively on the segmented parts, increasing the resolution of the curve skeleton extraction in order to have more detailed models after the ﬁrst rough classiﬁcation of the parts. We plan to segment automatically in this way hands and feet. Results obtained are promising even if preliminary and a lot of further work is planned to carry on the whole body scanner segmentation pipeline. We plan, in fact, to characterize better the position of the characteristic points on the curve-skeleton by building statistical models of the skeleton features and registering them with the acquired data for a precise localization.
A) (b) Fig. 5. 8. The number of iterations is set to 6. 3D models obtained by adding Gaussian noise to the original 3D models. 02 ¯, where ¯ is given by Eq. (1). Geometric Mesh Denoising via Multivariate Kernel Diﬀusion 29 In practical applications, the covariance matrix Hi given by Eq. (6) may become singular. To circumvent this singularity problem and also to ensure the stability of the proposed algorithm, we use a regularized covariance matrix as follows Hi = Hi + λ I (7) where I is a 3 × 3 identity matrix and λ is a positive regularization parameter.
4 Ball and Player Trajectory Computation The second algorithmic procedure runs on the processing unit with the supervisor function.
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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