An Investigation of Model Bias in 3D Face Tracking

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An Investigation of Model Bias in 3D Face Tracking
3D tracking of faces in video streams is a difficult problem that can be assisted with the use of a priori knowledge of the structure and appearance of the subject’s face at predefined poses (keyframes). This paper provides an extensive analysis of a state-of-the-art keyframebased tracker: quantitatively demonstrating the dependence of tracking performance on underlying mesh accuracy, number and coverage of reliably matched feature points, and initial keyframe alignment. Tracking with a generic face mesh can introduce an erroneous bias that leads to degraded tracking performance when the subject’s out-of-plane motion is far from the set of keyframes. To reduce this bias, we show how online refinement of a rough estimate of face geometry may be used to re-estimate the 3d keyframe features, thereby mitigating sensitivities to initial keyframe inaccuracies in pose and geometry. An in-depth analysis is performed on sequences of faces with synthesized rigid head motion. Subsequent tri...
Douglas Fidaleo, Gérard G. Medioni, Pascal
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where AMFG
Authors Douglas Fidaleo, Gérard G. Medioni, Pascal Fua, Vincent Lepetit
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