Automatic landmarking of 2D images

face detection system

Facial landmark detection, or localisation, is an essential preprocessing step in any automatic face analysis system. A 2D FLD algorithm is usually applied to the content of a face bounding box output by a face detector, and attempts to locate the positions of a set of pre-defined landmarks (key points) such as eyebrows, eye centres, nose tip or mouth corners of the facial parts in a 2D image.

We have made three contributions to the field:

  1. Feng, Hu, Kittler, Christmas, Wu: Cascaded Collaborative Regression for Robust Facial Landmark Detection Trained Using a Mixture of Synthetic and Real Images With Dynamic Weighting. IEEE Transactions on Image Processing, Vol.24(11), 2015, pp:3425-3440.
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  3. Feng, Huber, Kittler, Christmas and Wu: Random Cascaded-Regression Copse for Robust Facial Landmark Detection. IEEE Signal Processing Letters, Vol.22(1), 2015, pp:76-80.
  4. Feng, Kittler, Christmas, Wu and Pfeiffer: Automatic face annotation by multilinear AAM with Missing Values. ICPR, 2012, pp: 2586-2589

Zhenhua Feng, Bill Christmas
Last modified: Thu Jul 16 11:55:43 BST 2015