SHREC'08 entry: 3D face recognition using facial contour curves

In this work we compute the similarity of 3D faces using a set of eight contour curves. These contours were selected and matched using our 3D face matching framework. In previous work, we performed extensive research to the selection of distinctive facial curves for 3D face matching. To relate the performance of several of these curves to other face matching methods, we participated the Shape Retrieval Contest (SHREC) of 3D face scans. Within this contest we have used a set of eight C-contours and tested their face retrieval performance using two different distance measures. In an attempt to increase the expression invariance of these curves, we employed our 3D face matching framework to match either 100% of the selected features or the subset of the best 60% of the selected features. Results show that the selected distance measure can have a great influence on the distinctiveness of facial curves. In case of large variations in facia) expressiveness, the subset of the best 60% of the features increases the overall performance. With a recognition rate of 91.1% and a mean average precision of 0.693 our method performs reasonably well compared to other methods.