This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Search for Publication

Year(s) from:  to 
Keywords (separated by spaces):

On-line Face Tracking Using a Feature-Driven Level Set

D. Magee and B. Leibe
British Machine Vision Conference (BMVC'03)
Norwich, UK, September 2003


An efficient and general framework for the incorporation of statistical prior information, based on a wide variety of detectable point features, into level set based object tracking is presented. Level set evolution is based on the maximisation of a set of likelihoods on mesh values at features, which are located using a stochastic sampling process. This evolution is based on the interpolation of likelihood gradients using kernels centred at the features. Feature detectors implemented are based on moments of colour histogram segmented images and learned image patches located using normalised correlation, although a wide variety of feature detectors could be used. A computationally efficient level set implementation is presented along with a method for the incorporation of a motion model into the scheme.

Download in pdf format
  author = {D. Magee and B. Leibe},
  title = {On-line Face Tracking Using a Feature-Driven Level Set},
  booktitle = {British Machine Vision Conference (BMVC'03)},
  year = {2003},
  month = {September},
  keywords = {}