Accelerating Active Shape Model Using GPU for Facial Extraction in Video
Refereed conference paper presented and published in conference proceedings

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AbstractIn this paper, we present a novel parallel implementation of Active Shape Model (ASM) on GPU for massive facial feature extractions in video or image sequence. With the Compute Unified Device Architecture (CUDA)-enabled GPU, the acceleration is significant and reported a 48 times performance boost comparing to a CPU implementation. We adopt the hardware built-in bilinear interpolation of texture to shorten the time for a large number of image scale transform operations. Then, a GPU-based parallel mahalanobis distance calculation is introduced in the searching process, and this enables most of the computations to be performed simultanously. As a result, we can achieve real-time performance in our video-driven 3D facial animation system.
All Author(s) ListLi JA, Lu Y, Pu B, Xie YM, Qin J, Pang WM, Heng PA
Name of ConferenceIEEE International Conference on Intelligent Computing and Intelligent Systems
Start Date of Conference20/11/2009
End Date of Conference22/11/2009
Place of ConferenceShanghai
Country/Region of ConferenceChina
Pages522 - 526
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesComputer Science; Computer Science, Artificial Intelligence

Last updated on 2020-29-05 at 02:10