Empirical Inference Conference Paper 2009

Markerless 3D Face Tracking (DAGM 2009)

We present a novel algorithm for the markerless tracking of deforming surfaces such as faces. We acquire a sequence of 3D scans along with color images at 40Hz. The data is then represented by implicit surface and color functions, using a novel partition-of-unity type method of efficiently combining local regressors using nearest neighbor searches. Both these functions act on the 4D space of 3D plus time, and use temporal information to handle the noise in individual scans. After interactive registration of a template mesh to the first frame, it is then automatically deformed to track the scanned surface, using the variation of both shape and color as features in a dynamic energy minimization problem. Our prototype system yields high-quality animated 3D models in correspondence, at a rate of approximately twenty seconds per timestep. Tracking results for faces and other objects are presented.

Author(s): Walder, C. and Breidt, M. and Bülthoff, HH. and Schölkopf, B. and Curio, C.
Book Title: Pattern Recognition, Lecture Notes in Computer Science, Vol. 5748
Journal: Pattern Recognition: 31st DAGM Symposium
Pages: 41-50
Year: 2009
Month: September
Day: 0
Editors: J Denzler and G Notni and H S{\"u}sse
Publisher: Springer
Bibtex Type: Conference Paper (inproceedings)
Address: Berlin, Germany
DOI: 10.1007/978-3-642-03798-6_5
Event Name: 31st Symposium of the German Association for Pattern Recognition (DAGM 2009)
Event Place: Jena, Germany
Digital: 0
Electronic Archiving: grant_archive
Institution: Lecture Nores in Computer Science
ISBN: 978-3-642-03798-6
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex

@inproceedings{5899,
  title = {Markerless 3D Face Tracking (DAGM 2009)},
  journal = {Pattern Recognition: 31st DAGM Symposium},
  booktitle = {Pattern Recognition, Lecture Notes in Computer Science, Vol. 5748
  },
  abstract = {We present a novel algorithm for the markerless tracking of deforming surfaces such as faces. We acquire a sequence of 3D scans along with color images at 40Hz. The data is then represented by implicit surface and color functions, using a novel partition-of-unity type method of efficiently combining local regressors using nearest neighbor searches. Both these functions act on the 4D space of 3D plus time, and use temporal information to handle the noise in individual scans. After interactive registration of a template mesh to the first frame, it is then automatically deformed to track the scanned surface, using the variation
  of both shape and color as features in a dynamic energy minimization
  problem. Our prototype system yields high-quality animated 3D models in correspondence, at a rate of approximately twenty seconds per
  timestep. Tracking results for  faces and other objects are presented.},
  pages = {41-50},
  editors = {J Denzler and G Notni and H S{\"u}sse},
  publisher = {Springer},
  organization = {Max-Planck-Gesellschaft},
  institution = {Lecture Nores in Computer Science},
  school = {Biologische Kybernetik},
  address = {Berlin, Germany},
  month = sep,
  year = {2009},
  slug = {5899},
  author = {Walder, C. and Breidt, M. and B{\"u}lthoff, HH. and Sch{\"o}lkopf, B. and Curio, C.},
  month_numeric = {9}
}