Dynamic tracking of facial expressions using adaptive, overlapping subspaces

Dimitris Metaxas, Atul Kanaujia, Zhiguo Li

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

1 Scopus citations


We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear subspaces. The learned subspaces adaptively adjust to the subject by tracking the shapes independently using Kanade Lucas Tomasi(KLT) point tracker. The novelty of our approach is that the tracking of feature points is used to generate independent training examples for updating the learned shape manifold and the appearance model. We use landmark based shape analysis to train a Gaussian mixture model over the aligned shapes and learn a Point Distribution Model(PDM) for each of the mixture components. The target 2D shape is searched by first maximizing the mixture probability density for the local feature intensity profiles along the normal followed by constraining the global shape using the most probable PDM cluster. The feature shapes are robustly tracked across multiple frames by dynamically switching between the PDMs. The tracked 2D facial features are used deform the 3D face mask.The main advantage of the 3D deformable face models is the reduced dimensionality. The smaller number of degree of freedom makes the system more robust and enables capturing subtle facial expressions as change of only a few parameters. We demonstrate the results on tracking facial features and provide several empirical results to validate our approach. Our framework runs close to real time at 25 frames per second.

Original languageEnglish (US)
Title of host publicationComputational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783540725831
StatePublished - 2007
Event7th International Conference on Computational Science, ICCS 2007 - Beijing, China
Duration: May 27 2007May 30 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4487 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other7th International Conference on Computational Science, ICCS 2007

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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