Video-rate three-dimensional (3-D) acquisition is desirable, in particular for capturing the mouth's shape when modeling the vocal tract. In a new structured light technique, scenes are illuminated by an array of circular spots which are color encoded to resolve spatial ambiguity. The position and shape of the imaged spots depend on the location and orientation of the illuminated 3-D surface. We present a novel 3-D Hough transform (HT) to detect 3-D surface location and orientation via the imaged spots, with voting constraints applied to maximize potential accuracy. This new technique is demonstrated to successfully extract the 3-D data for a moving face from images acquired at video-rate.

Abstract-Matching pursuits over a basis of separable Gabor functions has been demonstrated to outperform DCT methods for displaced frame difference coding for video compression. Unfortunately, apart from very low bit-rate applications, the algorithm involves an extremely high computational load. This paper contains original contribution to the issues of dictionary selection and fast implementation for matching pursuits video coding. First, it is shown that the PSNR performance of existing matching pursuits codecs can be improved and the implementation cost reduced by a better selection of dictionary functions. Secondly, dictionary factorization is put forward to further reduce implementation costs. A reduction of the computational load by a factor of 20 is achieved compared to implementations reported to date. For a majority of test conditions, this reduction is supplemented by an improvement in reconstruction quality. Finally, a pruned full-search algorithm is introduced, which offers significant quality gains compared to the better-known heuristic fast-search algorithm, while keeping the computational cost low.Index Terms-Displaced frame difference, low-complexity algorithm, matching pursuit, pruned full search, video coding.

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