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Titlebook: Computer Analysis of Images and Patterns; 12th International C Walter G. Kropatsch,Martin Kampel,Allan Hanbury Conference proceedings 2007

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樓主: supplementary
11#
發(fā)表于 2025-3-23 09:41:40 | 只看該作者
Human Action Recognition in Table-Top Scenarios : An HMM-Based Analysis to Optimize the Performancenumber of states and Gaussian for HMM and the number of training iterations, are considered for optimization of the recognition rate with 5 different feature sets on our motion capture data set from 10 persons.
12#
發(fā)表于 2025-3-23 17:12:38 | 只看該作者
13#
發(fā)表于 2025-3-23 18:37:12 | 只看該作者
Ostdeutsche Frauen im Transformationsproze?as instructions are only fired when the data needed for these instructions are available. Here we present a method to speed-up low level motion detection algorithms. This method is based on pixel change instead of full image processing and good speed-up is achieved.
14#
發(fā)表于 2025-3-23 22:42:20 | 只看該作者
15#
發(fā)表于 2025-3-24 06:24:55 | 只看該作者
The Complexity of VLSI Computations, relative light transmission across the image plane due to fixed, partially-transparent objects. The resulting transmission map enables reconstruction of a video in which the occlusions have been removed. We present experimental results that compare the effectiveness and applicability of our two approaches.
16#
發(fā)表于 2025-3-24 08:08:23 | 只看該作者
R. P. Lewis,H. Boudoulas,P. Ruff,R. E. Katesal-world videos from an ecological source and proves useful in conceptualising and generalising video processing tasks. On a more significant note, this could be used in a framework for automatic video analysis in emerging infrastructures such as the Grid.
17#
發(fā)表于 2025-3-24 11:29:20 | 只看該作者
18#
發(fā)表于 2025-3-24 15:07:31 | 只看該作者
19#
發(fā)表于 2025-3-24 21:38:58 | 只看該作者
20#
發(fā)表于 2025-3-25 00:52:53 | 只看該作者
Ostdeutsche Frauen im Transformationsproze? framework based on the conditional random field, where the interaction strength can be adaptively adjusted in terms of data similarity of neighboring sites. Experimental results show that the proposed approach effectively fuses contextual dependencies in video sequences and significantly improves the accuracy of object detection.
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