articleIEEE Transactions on Image ProcessingDec 19, 2006Closed access

Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines

Aristotle University of Thessaloniki

PubMed
Indexed incrossrefpubmed

Abstract

In this paper, two novel methods for facial expression recognition in facial image sequences are presented. The user has to manually place some of Candide grid nodes to face landmarks depicted at the first frame of the image sequence under examination. The grid-tracking and deformation system used, based on deformable models, tracks the grid in consecutive video frames over time, as the facial expression evolves, until the frame that corresponds to the greatest facial expression intensity. The geometrical displacement of certain selected Candide nodes, defined as the difference of the node coordinates between the first and the greatest facial expression intensity frame, is used as an input to a novel…

Citation impact

687
total citations
FWCI
19.29
Percentile
100%
References
53
Citations per year

Authors

2

Topics & keywords

Keywords
  • Artificial intelligence
  • Facial expression
  • Support vector machine
  • Computer vision
  • Computer science
  • Pattern recognition (psychology)
  • Face (sociological concept)
  • Frame (networking)
No related works found for this paper.