Facial animation based on 2D shape regression

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We present a facial animation system for ordinary singlecameral videos based on 2D shape regression. Unlike some prior facial animation techniques, our system doesn’t need complex equipment. The system consists of firstly a Cascade Multi-Channel Convolutional Neural Network (CMC-CNN) model to accurately detect facial landmarks from 2D video frames. Based on these detected 2D points, the facial motion parameters, including the head pose and facial expressions, are recovered. Then the system animates a bone-driven 3D avatar with the facial motion parameters. Experiments show that our system can accurately detect facial landmarks and the animation results are visually plausible and similar to the user’s facial motion.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing – 17th Pacific-Rim Conference on Multimedia, PCM 2016, Proceedings
EditorsEnqing Chen, Yun Tie, Yihong Gong
PublisherSpringer Verlag
Pages33-42
Number of pages10
ISBN (Print)9783319488950
DOIs
StatePublished - 2016
Event17th Pacific-Rim Conference on Multimedia, PCM 2016 - Xi’an, China
Duration: 15 Sep 201616 Sep 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9917 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th Pacific-Rim Conference on Multimedia, PCM 2016
Country/TerritoryChina
CityXi’an
Period15/09/1616/09/16

Keywords

  • 3D avatars
  • Facial animation
  • Video tracking

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