Adjusting shape parameters using model-based optical flow residuals

Douglas DeCarlo, Dimitris Metaxas

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


We present a method for estimating the shape of a deformable model using the least-squares residuals from a model-based optical flow computation. This method is built on top of an estimation framework using optical flow and image features, where optical flow affects only the motion parameters of the model. Using the results of this computation, our new method adjusts all of the parameters so that the residuals from the flow computation are minimized. We present face tracking experiments that demonstrate that this method obtains a better estimate of shape compared to related frameworks.

Original languageEnglish (US)
Pages (from-to)814-823
Number of pages10
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number6
StatePublished - Jun 2002

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


  • Deformable models
  • Model-based optical flow
  • Nonrigid shape and motion estimation


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