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Titlebook: Consumer Depth Cameras for Computer Vision; Research Topics and Andrea Fossati,Juergen Gall,Kurt Konolige Book 2013 Springer-Verlag London

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發(fā)表于 2025-3-28 16:46:24 | 只看該作者
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發(fā)表于 2025-3-28 19:58:56 | 只看該作者
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發(fā)表于 2025-3-28 23:31:43 | 只看該作者
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發(fā)表于 2025-3-29 06:05:32 | 只看該作者
A Data-Driven Approach for Real-Time Full Body Pose Reconstruction from a Depth Cameracomes more feasible when using streams of 2.5D monocular depth images as provided by a depth camera. However, due to low resolution of and challenging noise characteristics in depth camera images as well as self-occlusions in the movements, the pose estimation task is still far from being simple. Fu
45#
發(fā)表于 2025-3-29 08:17:44 | 只看該作者
Home 3D Body Scans from a Single Kinect availability of 3D body models. Although there has been a great deal of interest recently in the use of active depth sensing cameras, such as the Microsoft Kinect, for human pose tracking, little has been said about the related problem of human shape estimation. We present a method for human shape
46#
發(fā)表于 2025-3-29 13:07:09 | 只看該作者
47#
發(fā)表于 2025-3-29 16:40:49 | 只看該作者
A Category-Level 3D Object Dataset: Putting the Kinect to Worktection dataset to the forefront. Such a dataset can be used for object recognition in a spirit usually reserved for the large collections of intensity images typically collected from the Internet. Here, we will review current 3D datasets and find them lacking in variation of scene, category, instan
48#
發(fā)表于 2025-3-29 22:49:10 | 只看該作者
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發(fā)表于 2025-3-30 00:41:37 | 只看該作者
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