The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
ImageMap: An Image Indexing Method Based on Spatial Similarity
IEEE Transactions on Knowledge and Data Engineering
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Head Modeling from Pictures and Morphing in 3D with Image Metamorphosis Based on Triangulation
CAPTECH '98 Proceedings of the International Workshop on Modelling and Motion Capture Techniques for Virtual Environments
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Face Recognition Using Range Images
VSMM '97 Proceedings of the 1997 International Conference on Virtual Systems and MultiMedia
Face Modeling and Recognition in 3-D
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Face recognition by fractal transformations
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Face recognition by independent component analysis
IEEE Transactions on Neural Networks
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Most face based biometric systems and the underlying recognition algorithms are often more suited for verification (one-to-one comparison) instead of identification (one-to-many comparison) purposes. This is even more true in case of large face database, as the computational cost of an accurate comparison between the query and a gallery of many thousands of individuals could be too high for practical applications. In this paper we present a 3D based face recognition method which relies on normal image to represent and compare face geometry. It features fast comparison time and good robustness to a wide range of expressive variations thanks to an expression weighting mask, automatically generated for each enrolled subject. To better address one-to-many recognition applications, the proposed approach is improved via DFT based indexing of face descriptors and k-d-tree based spatial access to clusters of similar faces. We include experimental results showing the effectiveness of the presented method in terms of recognition accuracy and the improvements in one-to-many recognition time achieved thanks to indexing and retrieval techniques applied to a large parametric 3D face database.