Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal
  Biometric Fusion Algorithms   Automatically verifying the identity of a person by means of biometrics is an
important application in day-to-day activities such as accessing banking
services and security control in airports. To increase the system reliability,
several biometric devices are often used. Such a combined system is known as a
multimodal biometric system. This paper reports a benchmarking study carried
out within the framework of the BioSecure DS2 (Access Control) evaluation
campaign organized by the University of Surrey, involving face, fingerprint,
and iris biometrics for person authentication, targeting the application of
physical access control in a medium-size establishment with some 500 persons.
While multimodal biometrics is a well-investigated subject, there exists no
benchmark for a fusion algorithm comparison. Working towards this goal, we
designed two sets of experiments: quality-dependent and cost-sensitive
evaluation. The quality-dependent evaluation aims at assessing how well fusion
algorithms can perform under changing quality of raw images principally due to
change of devices. The cost-sensitive evaluation, on the other hand,
investigates how well a fusion algorithm can perform given restricted
computation and in the presence of software and hardware failures, resulting in
errors such as failure-to-acquire and failure-to-match. Since multiple
capturing devices are available, a fusion algorithm should be able to handle
this nonideal but nevertheless realistic scenario. In both evaluations, each
fusion algorithm is provided with scores from each biometric comparison
subsystem as well as the quality measures of both template and query data. The
response to the call of the campaign proved very encouraging, with the
submission of 22 fusion systems. To the best of our knowledge, this is the
first attempt to benchmark quality-based multimodal fusion algorithms.

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The categories of this paper are: hep-th
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The categories of this paper are: econ
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: physics
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The categories of this paper are: adap-org
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The categories of this paper are: dg-ga
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The categories of this paper are: gr-qc
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The categories of this paper are: mtrl-th
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The categories of this paper are: plasm-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: cmp-lg
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The categories of this paper are: alg-geom