Multi-Modal Data Fusion for Person Authentication using SVM

Abstract

In the context of multi-modal person authentication, a set of experts (face recognizer, speaker recognizer, etc. ) give their opinion about the identity of an individual. The opinions of the experts can be combined to form a final decision (rejecting or accepting the claim). We show that the final decision is a binary classification problem and propose to solve it by a Support Vector Machine (SVM). We compare our approach with other proposed methods for an identical verification task and show that it leads to considerably higher performance

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