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Efficient Face and Facial Feature Tracking using Search Region Estimation

Efficient Face and Facial Feature Tracking using Search Region Estimation
Efficient Face and Facial Feature Tracking using Search Region Estimation
In this paper an intelligent and efficient combination of several methods are employed for face and facial feature tracking with the motivation for real time applications. Face tracking algorithm is based on color and connected component analysis. It is scale, pose and orientation invariant, and can be implemented in real time in controlled environments. The more challenging problem of facial feature tracking uses intensity based adaptive clustering on facial feature sub-images. New search region estimation for each sub-image is proposed. The technique employs facial expression aware eye sub-image prediction. The simulation results indicate that facial feature tracking is efficient with an average tracking rate of 99% with a three pixel range under different head movements such as translation, rotation, tilt, and scale changes. Furthermore it is robust under varying facial expressions and non-uniform illumination.
1149-1157
Direkoglu, Cem
b793e59b-4188-44b2-99c5-b4dedc46cfda
Demirel, Hasan
92546797-b36a-45d8-bd0d-b7117e22a357
Ozkaramanli, Huseyin
29c003d8-3d12-42d6-a4c8-c0ebff7c337f
Uyguroglu, Mustafa
c7ca769a-9537-45dd-9f4a-65736075d24f
Direkoglu, Cem
b793e59b-4188-44b2-99c5-b4dedc46cfda
Demirel, Hasan
92546797-b36a-45d8-bd0d-b7117e22a357
Ozkaramanli, Huseyin
29c003d8-3d12-42d6-a4c8-c0ebff7c337f
Uyguroglu, Mustafa
c7ca769a-9537-45dd-9f4a-65736075d24f

Direkoglu, Cem, Demirel, Hasan, Ozkaramanli, Huseyin and Uyguroglu, Mustafa (2005) Efficient Face and Facial Feature Tracking using Search Region Estimation. International Conference of Image Analysis and Recognition, LNCS 3656. pp. 1149-1157 .

Record type: Conference or Workshop Item (Other)

Abstract

In this paper an intelligent and efficient combination of several methods are employed for face and facial feature tracking with the motivation for real time applications. Face tracking algorithm is based on color and connected component analysis. It is scale, pose and orientation invariant, and can be implemented in real time in controlled environments. The more challenging problem of facial feature tracking uses intensity based adaptive clustering on facial feature sub-images. New search region estimation for each sub-image is proposed. The technique employs facial expression aware eye sub-image prediction. The simulation results indicate that facial feature tracking is efficient with an average tracking rate of 99% with a three pixel range under different head movements such as translation, rotation, tilt, and scale changes. Furthermore it is robust under varying facial expressions and non-uniform illumination.

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More information

Published date: 2005
Venue - Dates: International Conference of Image Analysis and Recognition, LNCS 3656, 2005-01-01
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 265216
URI: https://eprints.soton.ac.uk/id/eprint/265216
PURE UUID: e9b03620-5796-47e7-b2bf-18a56c4b6707

Catalogue record

Date deposited: 27 Feb 2008 18:09
Last modified: 18 Jul 2017 07:28

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Contributors

Author: Cem Direkoglu
Author: Hasan Demirel
Author: Huseyin Ozkaramanli
Author: Mustafa Uyguroglu

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