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Titlebook: Advances in Visual Computing; Third International George Bebis,Richard Boyle,Tom Malzbender Conference proceedings 2007 Springer-Verlag Be

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61#
發(fā)表于 2025-4-1 02:00:12 | 只看該作者
https://doi.org/10.1007/978-3-642-18562-5umber of vertices. Test results show that the new method leads to good interpolation results even for complicated data sets. The new method is demonstrated with the Catmull-Clark subdivision scheme. But with some minor modification, one should be albe to apply this method to other parametrizable sub
62#
發(fā)表于 2025-4-1 06:48:32 | 只看該作者
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發(fā)表于 2025-4-1 12:49:00 | 只看該作者
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發(fā)表于 2025-4-1 16:37:23 | 只看該作者
Conference proceedings 2007ck papers were solicited separately through the Organizing and Program Committees of each track. A total of 32 papers were accepted for oral presentation and 5 papers for poster presentation in the special tracks.
65#
發(fā)表于 2025-4-1 20:08:27 | 只看該作者
0302-9743 pecial track papers were solicited separately through the Organizing and Program Committees of each track. A total of 32 papers were accepted for oral presentation and 5 papers for poster presentation in the special tracks.978-3-540-76857-9978-3-540-76858-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
66#
發(fā)表于 2025-4-2 00:44:07 | 只看該作者
67#
發(fā)表于 2025-4-2 05:14:12 | 只看該作者
Robust Infants Face Tracking Using Active Appearance Models: A Mixed-State CONDENSATION Approache problem of tracking a face and its features in baby video sequences. A mixed state particle filtering scheme is proposed, where the distribution of observations is derived from an active appearance model. The mixed state approach combines several dynamic models in order to account for different oc
68#
發(fā)表于 2025-4-2 09:51:55 | 只看該作者
69#
發(fā)表于 2025-4-2 11:17:47 | 只看該作者
Using Gaussian Processes for Human Tracking and Action Classificationacker (GPAPF), which is an extension of the annealed particle filter tracker and uses Gaussian Process Dynamical Model (GPDM) in order to reduce the dimensionality of the problem, increase the tracker’s stability and learn the motion models. Motion of human body is described by concatenation of low
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