Analysis and compression of facial animation parameter set (FAPs)

Hai Tao, Homer Chen, Thomas Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a new representation of FAPs based on principal component analysis is proposed. Based on this compact representation, a FAPs compression scheme is designed. A facial expression recognition algorithm using recurrent neural network is also investigated. The inputs to the network are the most significant components of this new data representation. Experimental results show that computational complexity is reduced and expressions can be correctly recognized even with changed sampling rate.

Original languageEnglish (US)
Title of host publication1997 IEEE 1st Workshop on Multimedia Signal Processing, MMSP 1997
EditorsYao Wang, Amy R. Reibman, B. H. Juang, Tsuhan Chen, Sun-Yuan Kung
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages245-250
Number of pages6
ISBN (Electronic)0780337808, 9780780337800
DOIs
StatePublished - 1997
Event1st IEEE Workshop on Multimedia Signal Processing, MMSP 1997 - Princeton, United States
Duration: Jun 23 1997Jun 25 1997

Publication series

Name1997 IEEE 1st Workshop on Multimedia Signal Processing, MMSP 1997

Other

Other1st IEEE Workshop on Multimedia Signal Processing, MMSP 1997
Country/TerritoryUnited States
CityPrinceton
Period6/23/976/25/97

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology

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