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Robust Facial Feature Tracking

Authors: Fabrice Bourel; Claude C. Chibelushi; Adrian A. Low;

Robust Facial Feature Tracking

Abstract

We present a robust technique for tracking a set of pre-determined points on a human face. To achieve robustness, the Kanade-Lucas-Tomasi point tracker is extended and specialised to work on facial features by embedding knowledge about the configuration and visual characteristics of the face. The resulting tracker is designed to recover from the loss of points caused by tracking drift or temporary occlusion. Performance assessment experiments have been carried out on a set of 30 video sequences of several facial expressions. It is shown that using the original Kanade-Lucas-Tomasi tracker, some of the points are lost, whereas using the new method described in this paper, all lost points are recovered with no or little displacement error.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
30
Average
Top 10%
Average
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