Automated Registration of 3D Faces using Dense Surface Models

Dense surface models can be used to register unseen surfaces, using an algorithm which is a hybrid of iterative closest-point (ICP) and active shape model (ASM) fitting. In this paper we give details of this procedure and show how it can be improved by sequentially extending the transform group over which it operates. We also evaluate it for robustness to the position of the target and to shape variation across a set of unseen examples. The fit was successful on all 21 examples in our test set, with an average RMS error of 3.0mm. An initial comparison of 3 people landmarking the same scans suggests that this is within the normal landmark reproducibility range for 3D face scans.

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