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Cited by 592

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Person identification using multiple cues

Brunelli, R., Falavigna, D.·1995·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

This paper presents a person identification system based on acoustic and visual features. The system is organized as a set of non-homogeneous classifiers whose outputs are integrated after a normalization step. In particular, two classifiers based on acoustic features and three based on visual ones provide data for an integration module whose performance is evaluated. A novel technique for the integration of multiple classifiers at an hybrid rank/measurement level is introduced using HyperBF networks. Two different methods for the rejection of an unknown person are introduced. The performance of the integrated system is shown to be superior to that of the acoustic and visual subsystems. The resulting identification system can be used to log personal access and, with minor modifications, as an identity verification system.>

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Metadata

Authors
Brunelli, R., & Falavigna, D.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
1995-10
Volume
17
Issue
10
Pages
955-966
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
OpenAlex
W2024677982
Cited by
592
References
2
FWCI
15.46
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Person identification using multiple cues. https://app.cochat.ai/papers/10.1109/34.464560
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Brunelli, R., & Falavigna, D. (1995). Person identification using multiple cues. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.464560

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.