Pattern Recognition
On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Faces and Fingerprints for Personal Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Classification for Imprecise Environments
Machine Learning
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Learning Decision Trees Using the Area Under the ROC Curve
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Information fusion in biometrics
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Fingerprint and Speaker Verification Decisions Fusion
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Benchmarking a Reduced Multivariate Polynomial Pattern Classifier
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimising area under the ROC curve using gradient descent
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A support vector method for multivariate performance measures
ICML '05 Proceedings of the 22nd international conference on Machine learning
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Training a reciprocal-sigmoid classifier by feature scaling-space
Machine Learning
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Model-guided deformable hand shape recognition without positioning aids
Pattern Recognition
Score normalization in multimodal biometric systems
Pattern Recognition
Handbook of Face Recognition
Fusion of face and speech data for person identity verification
IEEE Transactions on Neural Networks
Universal approximation using incremental constructive feedforward networks with random hidden nodes
IEEE Transactions on Neural Networks
A feature extraction method for use with bimodal biometrics
Pattern Recognition
An online AUC formulation for binary classification
Pattern Recognition
Pattern Recognition
Hi-index | 0.01 |
The receiver operating characteristics (ROC) curve has been extensively used for performance evaluation in multimodal biometrics fusion. However, the processes of fusion classifier design and the final ROC performance evaluation are usually conducted separately. This has been inevitable because the ROC, when taken from the error counting point of view, does not have a well-posed structure linking to the fusion classifier of interest. In this work, we propose to optimize the ROC performance directly according to the fusion classifier design. The area under the ROC curve (AUC) will be used as the optimization objective since it provides a good representation of the ROC performance. Due to the piecewise cumulative structure of the AUC, a smooth approximate formulation is proposed. This enables a direct optimization of the AUC with respect to the classifier parameters. When a fusion classifier has linear parameters, computation of the solution to optimize a quadratic AUC approximation is surprisingly simple and yet effective. Our empirical experiments on biometrics fusion show strong evidences regarding the potential of the proposed method.