logo Idiap Research Institute        
 [BibTeX] [Marc21]
A Rao-Blackwellized Mixed State Particle Filter for Head Pose Tracking
Type of publication: Idiap-RR
Citation: sba:rr05-35
Number: Idiap-RR-35-2005
Year: 2005
Institution: IDIAP
Note: Published in ACM ICMI Workshop on Multimodal Multiparty Meeting Processing (MMMP,',','), 2005
Abstract: This paper presents a Rao-Blackwellized mixed state particle filter for joint head tracking and pose estimation. Rao-Blackwellizing a particle filter consists of marginalizing some of the variables of the state space in order to exactly compute their posterior probability density function. Marginalizing variables reduces the dimension of the configuration space and makes the particle filter more efficient and requires a lower number of particles. Experiments were conducted on our head pose ground truth video database consisting of people engaged in meeting discussions. Results from these experiments demonstrated benefits of the Rao-Blackwellized particle filter model with fewer particles over the mixed state particle filter model.
Userfields: ipdmembership={vision},
Projects Idiap
Authors Ba, Silèye O.
Odobez, Jean-Marc
Crossref by sba:mmmp:2005
Added by: [UNK]
Total mark: 0
  • sba-idiap-rr-05-35.pdf
  • sba-idiap-rr-05-35.ps.gz