3D Face Expression Estimation and Generation from 2D Image Based on a Physically Constraint Model

Takahiro ISHIKAWA; Shigeo MORISHIMA; Demetri TERZOPOULOS

3D Face Expression Estimation and Generation from 2D Image Based on a Physically Constraint Model

Takahiro ISHIKAWA, Shigeo MORISHIMA, Demetri TERZOPOULOS

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Muscle based face image synthesis is one of the most realistic approaches to the realization of a life-like agent in computers. A facial muscle model is composed of facial tissue elements and simulated muscles. In this model, forces are calculated effecting a facial tissue element by contraction of each muscle string, so the combination of each muscle contracting force decides a specific facial expression. This muscle parameter is determined on a trial and error basis by comparing the sample photograph and a generated image using our Muscle-Editor to generate a specific face image. In this paper, we propose the strategy of automatic estimation of facial muscle parameters from 2D markers'movements located on a face using a neural network. This corresponds to the non-realtime 3D facial motion capturing from 2D camera image under the physics based condition.

Publication: IEICE TRANSACTIONS on Information Vol.E83-D No.2 pp.251-258

Publication Date: 2000/02/25

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Type of Manuscript: PAPER

Category: Image Processing, Image Pattern Recognition

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Takahiro ISHIKAWA, Shigeo MORISHIMA, Demetri TERZOPOULOS, "3D Face Expression Estimation and Generation from 2D Image Based on a Physically Constraint Model" in IEICE TRANSACTIONS on Information, vol. E83-D, no. 2, pp. 251-258, February 2000, doi: .
Abstract: Muscle based face image synthesis is one of the most realistic approaches to the realization of a life-like agent in computers. A facial muscle model is composed of facial tissue elements and simulated muscles. In this model, forces are calculated effecting a facial tissue element by contraction of each muscle string, so the combination of each muscle contracting force decides a specific facial expression. This muscle parameter is determined on a trial and error basis by comparing the sample photograph and a generated image using our Muscle-Editor to generate a specific face image. In this paper, we propose the strategy of automatic estimation of facial muscle parameters from 2D markers'movements located on a face using a neural network. This corresponds to the non-realtime 3D facial motion capturing from 2D camera image under the physics based condition.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_2_251/_p

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@ARTICLE{e83-d_2_251,
author={Takahiro ISHIKAWA, Shigeo MORISHIMA, Demetri TERZOPOULOS, },
journal={IEICE TRANSACTIONS on Information},
title={3D Face Expression Estimation and Generation from 2D Image Based on a Physically Constraint Model},
year={2000},
volume={E83-D},
number={2},
pages={251-258},
abstract={Muscle based face image synthesis is one of the most realistic approaches to the realization of a life-like agent in computers. A facial muscle model is composed of facial tissue elements and simulated muscles. In this model, forces are calculated effecting a facial tissue element by contraction of each muscle string, so the combination of each muscle contracting force decides a specific facial expression. This muscle parameter is determined on a trial and error basis by comparing the sample photograph and a generated image using our Muscle-Editor to generate a specific face image. In this paper, we propose the strategy of automatic estimation of facial muscle parameters from 2D markers'movements located on a face using a neural network. This corresponds to the non-realtime 3D facial motion capturing from 2D camera image under the physics based condition.},
keywords={},
doi={},
ISSN={},
month={February},}

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TY - JOUR
TI - 3D Face Expression Estimation and Generation from 2D Image Based on a Physically Constraint Model
T2 - IEICE TRANSACTIONS on Information
SP - 251
EP - 258
AU - Takahiro ISHIKAWA
AU - Shigeo MORISHIMA
AU - Demetri TERZOPOULOS
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2000
AB - Muscle based face image synthesis is one of the most realistic approaches to the realization of a life-like agent in computers. A facial muscle model is composed of facial tissue elements and simulated muscles. In this model, forces are calculated effecting a facial tissue element by contraction of each muscle string, so the combination of each muscle contracting force decides a specific facial expression. This muscle parameter is determined on a trial and error basis by comparing the sample photograph and a generated image using our Muscle-Editor to generate a specific face image. In this paper, we propose the strategy of automatic estimation of facial muscle parameters from 2D markers'movements located on a face using a neural network. This corresponds to the non-realtime 3D facial motion capturing from 2D camera image under the physics based condition.
ER -