Inspired by Bertillon - Recognition Based on Anatomical Features from 3D Face Scans

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Inspired by Bertillon - Recognition Based on Anatomical Features from 3D Face Scans

Popis výsledku v původním jazyce

We present an automatic 3D face recognition algorithm that is inspired by Alphonse Bertillon's anthropometry. Our recognition pipeline consists of several steps. First, the facial landmarks such as the tip of the nose or the inner eye corners are detected. Subsequently the head rotation is compensated during the orientation normalization process. The facial features are extracted by performing 61 different measures. We also present a feature evaluation function that rates individual components of the feature vector. Finally, our results are compared with two other 3D face recognition methods. We show that the multi-algorithmic system consisting of the anatomical-based recognition together with the eigenfaces method and the recognition using histogram-based features reaches significantly better results than any of the employed methods individually.

Název v anglickém jazyce

Inspired by Bertillon - Recognition Based on Anatomical Features from 3D Face Scans

Popis výsledku anglicky

We present an automatic 3D face recognition algorithm that is inspired by Alphonse Bertillon's anthropometry. Our recognition pipeline consists of several steps. First, the facial landmarks such as the tip of the nose or the inner eye corners are detected. Subsequently the head rotation is compensated during the orientation normalization process. The facial features are extracted by performing 61 different measures. We also present a feature evaluation function that rates individual components of the feature vector. Finally, our results are compared with two other 3D face recognition methods. We show that the multi-algorithmic system consisting of the anatomical-based recognition together with the eigenfaces method and the recognition using histogram-based features reaches significantly better results than any of the employed methods individually.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 3rd International Workshop on Security and Communication Networks

ISBN

978-82-91313-67-2

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

53-58

Název nakladatele

Gjovik University College

Místo vydání

Gjovik

Místo konání akce

Gjovik

Datum konání akce

18. 5. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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