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Research at St Andrews

Multi-cue facial feature detection and tracking

Research output: Contribution to journalArticle

Author(s)

Jingying Chen, Bernard Tiddeman

School/Research organisations

Abstract

An efficient and robust facial feature detection and tracking system is presented in this paper. The system is capable of locating a human face automatically. Six facial feature points (pupils, nostrils and mouth corners) are detected and tracked using multiple cues including facial feature intensity and its probability distribution, geometric characteristics and motion information. In addition, in order to improve the robustness of the tracking system, a simple facial feature model is employed to estimate the relative face poses. This system has the advantage of automatically detecting the facial features and recovering the features lost during the tracking process. Encouraging results have been obtained using the proposed system.

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Details

Original languageEnglish
Pages (from-to)356-367
Number of pages12
JournalLecture Notes in Computer Science
Volume5099 LNCS
DOIs
Publication statusPublished - 2008

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