Computer Vision and Image Understanding
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Binary Image Metrics
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
A novel metrics based on information bottleneck principle for face retrieval
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
| Hi-index | 0.01 |
We describe a shape comparison method applicable to fast screening of large facial databases. The proposed technique derives holistic similarity measures without the explicit need of point-to-point correspondence thus delivering speed and tolerance to local non-rigid distortions. Specifically, we developed a face similarity measure derived as a variant of the Hausdorff distance by introducing the notion of a neighborhood function and associated penalties. Binarized edge representation is used to provide robustness to changes in illumination. Experimental results on a large facial data set demonstrate that our approach produces excellent search results even when less than 1% of the original grey-scale face image information is stored in the face database.