Combining Evidence in Multimodal Personal Identity Recognition Systems
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Journal of Cognitive Neuroscience
Multi-level fusion of audio and visual features for speaker identification
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Face recognition from images with high pose variations by transform vector quantization
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
A review of speech-based bimodal recognition
IEEE Transactions on Multimedia
Fusion of face and speech data for person identity verification
IEEE Transactions on Neural Networks
Usably secure, low-cost authentication for mobile banking
Proceedings of the Sixth Symposium on Usable Privacy and Security
| Hi-index | 0.00 |
We propose a low-complexity audio-visual person authentication framework based on multiple features and multiple nearest-neighbor classifiers, which instead of a single template uses a set of codebooks or collection of templates. Several novel highly-discriminatory speech and face image features are introduced along with a novel "text-conditioned" speaker recognition approach. Powered by discriminative scoring and a novel fusion method, the proposed MCCN method delivers not only excellent performance (0% EER) but also a significant separation between the scores of client and imposters as observed on trials run on a unique multilingual 120-user audio-visual biometric database created for this research.