Performance capture from sparse multi-view video
ACM SIGGRAPH 2008 papers
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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.