Localization of facial feature points is an important step for many subsequent facial image analysis tasks. In this paper, we proposed a new coarse-to-fine method for extracting 20 facial feature points from image sequences. In particular, the Viola-Jones face detection method is extended to detect small-scale facial components with wide shape variations, and linear Kalman filters are used to smoothly track the feature points by handling detection errors and head rotations. The proposed method achieved higher than 90% detection rate when tested on the BioID face database and the FG-NET facial expression database. Moreover, our method shows robust performance against the variation of face resolutions and facial expressions. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Zhan, C., Li, W., Ogunbona, P., & Safaei, F. (2007). Real-time facial feature point extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4810 LNCS, pp. 88–97). Springer Verlag. https://doi.org/10.1007/978-3-540-77255-2_11
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