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引用次数: 3

摘要

我们提出了一个新概念,使用最少数量的摄像机实现多视图摄像机(或3D视频)动态场景的3D重建,而不是目前需要几十台摄像机或高清晰度设备的技术方法。一个3D视频由一系列的3D模型组成,这些模型是由周围的一组摄像机捕捉到的。结果是一个视频,观察者可以自由选择他们的观点。这是一个无标记的动作捕捉系统,受试者不需要佩戴特殊设备。因此,该系统适用于非常广泛的应用(例如,娱乐,医学,体育等)。使用基于图像的多视图立体重建技术(MVS)获得三维模型。MVS的性能取决于从不同视点拍摄的图像的质量和数量。由于图像之间必须找到立体对应关系,如果由于缺乏相机视图或光照变化而导致立体照片一致性较弱,则重建失败:一致的信息是必要的。
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Minimal 3D video
We present a new concept that achieves the 3D reconstruction of dynamic scenes from multi-view video cameras (or 3D videos) using a minimal number of cameras, as opposed to the present state of the art approaches which require either several tens of cameras or high definition devices. A 3D video consists of a sequence of 3D models in motion captured by a surrounding set of video cameras. The result is a video where observers can choose freely their viewpoints. It is a markerless motion capture system where subjects do not need to wear special equipment. Hence, this system suits to a very wide range of applications (e.g. entertainment, medicine, sports, and so on). The 3D models are obtained using image-based multi-view stereo reconstruction techniques (or MVS). The performance of MVS relies on the quality and quantity of images taken from different viewpoints. As stereo correspondences have to be found between the images, the reconstruction fails in the case of weak stereo photo-consistency due to lack of camera views or lighting variations: consistent information is necessary.
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