Facial Feature Detection and Tracking with a 3D Constrained
Files
Date issued
2010
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Václav Skala - UNION Agency
Abstract
In this paper, we describe a system for facial feature detection and tracking using a 3D extension of the Constrained Local Model
(CLM) [Cris 06, Cris 08] algorithm. The use of a 3D shape model allows improved tracking through large head rotations. CLM
uses a joint shape and texture appearance model to generate a set of region template detectors. A search is then performed in
the global pose / shape space using these detectors. The proposed extension uses multiple appearance models from different
viewpoints and a single 3D shape model. During fitting or tracking the current estimate of pose is used to select the appropriate
appearance model. We demonstrate our results by fitting the model to image sequences with large head rotations. The results
show that the proposed 3D constrained local model algorithm improves the performance of the original CLM algorithm for
videos with large out-of-plane head rotations.
Description
Subject(s)
3D tvarový model, model obličeje, sledování obličejových znaků, detekce obličejových znaků
Citation
WSCG 2010: Full Papers Proceedings: 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS, p. 181-188