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General borda count for multi-biometric retrieval

Damer, Naser and Terhorst, Philipp and Braun, Andreas and Kuijper, Arjan (2017):
General borda count for multi-biometric retrieval.
pp. 420-428, 2017 IEEE International Joint Conference on Biometrics (IJCB), Denver, USA, 01.-04. Oct. 2017, DOI: 10.1109/BTAS.2017.8272726,
[Conference or Workshop Item]

Abstract

Indexing of multi-biometric data is required to facilitate fast search in large-scale biometric systems. Previous works addressing this issue were challenged by including biometric sources of different nature, utilizing the knowledge about the biometric sources, and optimizing and tuning the retrieval performance. This work presents a generalized multi-biometric retrieval approach that adapts the Borda count algorithm within an optimizable structure. The approach was tested on a database of 10k reference and probe instances of the left and the right irises. The experiments and comparisons to five baseline solutions proved to achieve advances in terms of general indexing performance, tunability to certain operating points, and response to missing data. A clear advantage of the proposed solution was noticed when faced by candidate lists of low quality.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Damer, Naser and Terhorst, Philipp and Braun, Andreas and Kuijper, Arjan
Title: General borda count for multi-biometric retrieval
Language: English
Abstract:

Indexing of multi-biometric data is required to facilitate fast search in large-scale biometric systems. Previous works addressing this issue were challenged by including biometric sources of different nature, utilizing the knowledge about the biometric sources, and optimizing and tuning the retrieval performance. This work presents a generalized multi-biometric retrieval approach that adapts the Borda count algorithm within an optimizable structure. The approach was tested on a database of 10k reference and probe instances of the left and the right irises. The experiments and comparisons to five baseline solutions proved to achieve advances in terms of general indexing performance, tunability to certain operating points, and response to missing data. A clear advantage of the proposed solution was noticed when faced by candidate lists of low quality.

Uncontrolled Keywords: Biometric fusion, Multimedia indexing, Biometric identification systems, Multibiometrics
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 2017 IEEE International Joint Conference on Biometrics (IJCB)
Event Location: Denver, USA
Event Dates: 01.-04. Oct. 2017
Date Deposited: 04 May 2020 12:11
DOI: 10.1109/BTAS.2017.8272726
Official URL: https://ieeexplore.ieee.org/document/8272726
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