Decision fusion using a multi-linear classifier

The contribution of this paper is twofold: (1) to formulate a fusion problem encountered in the design of a multi-modal identity verification system as a particular classification problem, (2) to propose a simple classifier to solve this problem. The multi-modal identity verification system under consideration is built of d modalities in parallel, each one delivering as output a scalar number, called score, stating how much the claimed identity is verified. A fusion module receiving as input the d scores has to take a binary decision: accept or reject identity. We have formulated the design of this fusion module as a particular classification problem and developed a classifier based on a combination of half-spaces in the d-dimensional space to solve the problem. We call this classifier multi-linear classifier in reference to the use of several half-spaces, each one building a linear classifier. The performance of the fusion module has been evaluated on a multi-modal database.

Published in:
1st International Conference on Multisource-Multisensor Data Fusion
Presented at:
1st International Conference on Multisource-Multisensor Data Fusion

 Record created 2006-03-10, last modified 2018-03-17

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