In the past few years, top-down approaches have led to great successes in marker-less human motion capture (mocap). The term "top-down" means that a 3D reference surface (either generic or user specific) is pre-defined, and one has to track the motions (either surface deformations or skeletal poses) according to the observed 2D/3D data at each frame. The following videos demonstrate the examples of top-down approaches, using 3D visual hulls as input data:
Input visual hulls come from frame-wise 3D reconstructions using silhouettes from multiple cameras. A typical top-down tracking pipeline is illustrated in the right figure (top). Background subtraction therefore plays a crucial role, and consequently limits the applications to stay in indoor studios. |
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Title: | Multi-View Human Poses/Shape Tracking without Background Subtraction: a top-down approach |
Abstract: | A typical top-down human motion tracking pipeline requires good back subtraction, and therefore limits the applications to stay in indoor studios. In order to alleviate such a constraint, in this project we investigate the possibility to recover human motions directly with images. The 3D surfaces are expected to be textured, or at least contain per-vertex color information. Thus, the problem amounts to maximizing the similarity between the projected texture of surfaces and the image observations. |
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Director: | Prof. Dr. Nassir Navab |
Supervisor: | Chun-Hao Paul Huang, Dr. Slobodan Ilic |
Type: | Hiwi |
Area: | Computer Vision |
Status: | finished |
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