Signal-level Fusion for Indexing and Retrieval of Facial Biometric Data

• URL: http://arxiv.org/abs/2103.03692v1
• Date: Fri, 5 Mar 2021 14:06:54 GMT
• Title: Signal-level Fusion for Indexing and Retrieval of Facial Biometric Data
• Authors: Pawel Drozdowski, Fabian Stockhardt, Christian Rathgeb, Christoph Busch
• Abstract summary: The proposed method is extensively evaluated on publicly available databases using open-source and commercial off-the-shelf recognition systems. The results show that using the proposed method, the computational workload can be reduced down to around 30%.
• Score: 17.297562114613505
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The growing scope, scale, and number of biometric deployments around the world emphasise the need for research into technologies facilitating efficient and reliable biometric identification queries. This work presents a method of indexing biometric databases, which relies on signal-level fusion of facial images (morphing) to create a multi-stage data-structure and retrieval protocol. By successively pre-filtering the list of potential candidate identities, the proposed method makes it possible to reduce the necessary number of biometric template comparisons to complete a biometric identification transaction. The proposed method is extensively evaluated on publicly available databases using open-source and commercial off-the-shelf recognition systems. The results show that using the proposed method, the computational workload can be reduced down to around 30%, while the biometric performance of a baseline exhaustive search-based retrieval is fully maintained, both in closed-set and open-set identification scenarios.

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