Multi-cue facial feature detection and tracking

Jingying Chen*, Bernard Tiddeman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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.

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


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