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Titlebook: Computer Vision - ECCV 2002; 7th European Confere Anders Heyden,Gunnar Sparr,Peter Johansen Conference proceedings 2002 Springer-Verlag Ber

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21#
發(fā)表于 2025-3-25 06:50:58 | 只看該作者
Conference proceedings 2002onferences have been very successful, making ECCV a major event to the computer vision community. ECCV 2002 was the seventh in the series. The privilege of organizing it was shared by three universities: The IT University of Copenhagen, the University of Copenhagen, and Lund University, with the con
22#
發(fā)表于 2025-3-25 08:13:34 | 只看該作者
23#
發(fā)表于 2025-3-25 12:09:22 | 只看該作者
24#
發(fā)表于 2025-3-25 19:23:46 | 只看該作者
https://doi.org/10.1057/9780230281417be replaced by a guided search. Guidance of the search is based on readily-available information which is usually discarded, but can significantly reduce the search time. This guided-sampling algorithm is further specialised for tracking of multiple motions, for which results are presented.
25#
發(fā)表于 2025-3-25 22:21:34 | 只看該作者
26#
發(fā)表于 2025-3-26 01:12:51 | 只看該作者
27#
發(fā)表于 2025-3-26 04:29:46 | 只看該作者
28#
發(fā)表于 2025-3-26 09:59:49 | 只看該作者
Time-Recursive Velocity-Adapted Spatio-Temporal Scale-Space Filtersxternal warping mechanisms or keeping extended temporal buffers of the past. The approach can thus be seen as a natural extension of recursive scale-space filters from pure temporal data to spatio-temporal domains.
29#
發(fā)表于 2025-3-26 16:43:16 | 只看該作者
Adaptive Rest Condition Potentials: Second Order Edge-Preserving Regularizationh an adaptive rest condition. Efficient algorithms for computing the solution, and examples illustrating the performance of this scheme, compared with other known regularization schemes are presented as well.
30#
發(fā)表于 2025-3-26 16:51:45 | 只看該作者
Multimodal Data Representations with Parameterized Local Structuresponents are adaptively selected from the training data through a progressive density approximation procedure, which leads to the maximum likelihood estimate of the underlying density. We show results on both synthetic and real training sets, and demonstrate that the proposed scheme has the ability to reveal important structures of the data.
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