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Recovering Non-Rigid 3D Shape from Image Streams

11 years 1 months ago
Recovering Non-Rigid 3D Shape from Image Streams
This paper addresses the problem of recovering 3D non-rigid shape models from image sequences. For example, given a video recording of a talking person, we would like to estimate a 3D model of the lips and the full head and its internal modes of variation. Many solutions that recover 3D shape from 2D image sequences have been proposed; these so-called structure-from-motion techniques usually assume that the 3D object is rigid. For example, Tomasi and Kanade's factorization technique is based on a rigid shape matrix, which produces a tracking matrix of rank 3 under orthographic projection. We propose a novel technique based on a non-rigid model, where the 3D shape in each frame is a linear combination of a set of basis shapes. Under this model, the tracking matrix is of higher rank, and can be factored in a three step process to yield to pose, configuration and shape. We demonstrate this simple but effective algorithm on video sequences of speaking people. We were able to recover ...
Christoph Bregler, Aaron Hertzmann, Henning Bierma
Added 12 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 2000
Where CVPR
Authors Christoph Bregler, Aaron Hertzmann, Henning Biermann
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