%0 Conference Paper %1 torma2002 %A Torma, P. %A Szepesvári, Cs. %B Proc. First Hungarian Computer Graphics and Geometry Conference %C Budapest, Hungary %D 2002 %K application filtering, particle vision, %P 10--16 %T Towards Facial Pose Tracking %X This paper presents a novel facial-pose tracking algorithm using LS-N-IPS (Local Search N-Interacting Particle System), an algorithm that has been introduced recently by the authors. LS-N-IPS is a probabilistic tracking algorithm that keeps track of a number of alternative hypotheses at any time, the particles. LS-N-IPS has three components: a dynamical model, an observation model, and a local-search operator that has to be chosen by the algorithm designer. The main novelty of the algorithm presented here is that it relies on shading information to guide the local search procedure, the idea of the search being to apply a sort-of Hough-transformation to the mapping that renders poses to images. Here we introduce this algorithm and report results on the task of tracking of synthetic facial masks using grey-scale image sequences.

@inproceedings{torma2002, abstract = {This paper presents a novel facial-pose tracking algorithm using LS-N-IPS (Local Search N-Interacting Particle System), an algorithm that has been introduced recently by the authors. LS-N-IPS is a probabilistic tracking algorithm that keeps track of a number of alternative hypotheses at any time, the particles. LS-N-IPS has three components: a dynamical model, an observation model, and a local-search operator that has to be chosen by the algorithm designer. The main novelty of the algorithm presented here is that it relies on shading information to guide the local search procedure, the idea of the search being to apply a sort-of Hough-transformation to the mapping that renders poses to images. Here we introduce this algorithm and report results on the task of tracking of synthetic facial masks using grey-scale image sequences.}, added-at = {2020-03-17T03:03:01.000+0100}, address = {Budapest, Hungary}, author = {Torma, P. and Szepesv{\'a}ri, {Cs}.}, biburl = {https://www.bibsonomy.org/bibtex/24fed67ccbf000c58c483441e83eb0ce9/csaba}, booktitle = {Proc. First Hungarian Computer Graphics and Geometry Conference}, date-modified = {2010-09-02 13:09:16 -0600}, interhash = {d863fe432de752b096216827371ff4ba}, intrahash = {4fed67ccbf000c58c483441e83eb0ce9}, keywords = {application filtering, particle vision,}, owner = {Beata}, pages = {10--16}, pdf = {papers/MaskShadeLS.pdf}, timestamp = {2020-03-17T03:03:01.000+0100}, title = {Towards Facial Pose Tracking}, year = 2002 }