Accelerating active shape model using GPU for facial extraction in video

Jian Li, Yuqiang Lu, Bo Pu, Yongming Xie, Jing Qin, Wai Man Pang, Pheng Ann Heng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
Pages522-526
Number of pages5
Volume4
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009 - Shanghai, China
Duration: 20 Nov 200922 Nov 2009

Conference

Conference2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009
CountryChina
CityShanghai
Period20/11/0922/11/09

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering

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