Accelerating Active Shape Model Using GPU for Facial Eztraction in Video
In 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.
Jian Li Yuqiang Lu Bo Pu Yongming Xie Jing Qin Wai-Man Pang Pheng-Ann Heng
Shenzhen Institute of Advanced Integration Technology Chinese Academy of Sciences/ The Chinese Unive School of Computer Science and Engineering University of Electronic Science and Technology of China Shenzhen Institute of Advanced Integration Technology Chinese Academy of Sciences/ The Chinese Unive Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Shenzhen Institute of Advanced Integration Technology Chinese Academy of Sciences/ The Chinese Unive
国际会议
上海
英文
3051-3055
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）