Modelling facial colour and identity with Gaussian mixtures

Stephen J. McKenna; Shaogang Gong; Yogesh Raja

doi:10.1016/S0031-3203(98)00066-1

Modelling facial colour and identity with Gaussian mixtures

Stephen J. McKenna, Shaogang Gong, Yogesh Raja

Research output: Contribution to journal › Article › peer-review

172 Citations (Scopus)

Abstract

An integrated system for the acquisition, normalisation and recognition of moving faces in dynamic scenes is introduced. Four face recognition tasks are defined and it is argued that modelling person-specific probability densities in a generic face space using mixture models provides a technique applicable to all four tasks. The use of Gaussian colour mixtures for face detection and tracking is also described. Results are presented using data from the integrated system.

Original language	English
Pages (from-to)	1883-1892
Number of pages	10
Journal	Pattern Recognition
Volume	31
Issue number	12
DOIs	https://doi.org/10.1016/S0031-3203(98)00066-1
Publication status	Published - 1 Dec 1998

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10.1016/S0031-3203(98)00066-1

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title = "Modelling facial colour and identity with Gaussian mixtures",

abstract = "An integrated system for the acquisition, normalisation and recognition of moving faces in dynamic scenes is introduced. Four face recognition tasks are defined and it is argued that modelling person-specific probability densities in a generic face space using mixture models provides a technique applicable to all four tasks. The use of Gaussian colour mixtures for face detection and tracking is also described. Results are presented using data from the integrated system.",

author = "McKenna, {Stephen J.} and Shaogang Gong and Yogesh Raja",

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AU - Raja, Yogesh

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N2 - An integrated system for the acquisition, normalisation and recognition of moving faces in dynamic scenes is introduced. Four face recognition tasks are defined and it is argued that modelling person-specific probability densities in a generic face space using mixture models provides a technique applicable to all four tasks. The use of Gaussian colour mixtures for face detection and tracking is also described. Results are presented using data from the integrated system.

AB - An integrated system for the acquisition, normalisation and recognition of moving faces in dynamic scenes is introduced. Four face recognition tasks are defined and it is argued that modelling person-specific probability densities in a generic face space using mixture models provides a technique applicable to all four tasks. The use of Gaussian colour mixtures for face detection and tracking is also described. Results are presented using data from the integrated system.

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DO - 10.1016/S0031-3203(98)00066-1

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VL - 31

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EP - 1892

JO - Pattern Recognition

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Modelling facial colour and identity with Gaussian mixtures

Abstract

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