The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Desenvolvemos um novo sistema de rastreamento facial humano que opera em tempo real a uma taxa de quadros de vídeo sem a necessidade de nenhum hardware especial. A abordagem é baseada no uso da álgebra de Lie e utiliza pontos característicos tridimensionais na face humana alvo. Supõe-se que o modelo facial estimado aproximadamente (coordenadas relativas dos pontos característicos tridimensionais) seja conhecido. Primeiro, as posições iniciais dos recursos da face são determinadas usando uma técnica de ajuste de modelo. Em seguida, o rastreamento é operado pela seguinte sequência: (1) capturar o novo quadro de vídeo e renderizar os pontos característicos no plano da imagem; (2) busca por novas posições dos pontos característicos no plano da imagem; (3) obter a matriz euclidiana do vetor em movimento e a informação tridimensional dos pontos; e (4) girar e transladar os pontos característicos usando a matriz euclidiana e renderizar os novos pontos no plano da imagem. O algoritmo chave deste rastreador é estimar a matriz euclidiana usando uma técnica de mínimos quadrados baseada na álgebra de Lie. O rastreador resultante teve um desempenho muito bom na tarefa de rastrear um rosto humano.
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Akira INOUE, Tom DRUMMOND, Roberto CIPOLLA, "Real Time Feature-Based Facial Tracking Using Lie Algebras" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 12, pp. 1733-1738, December 2001, doi: .
Abstract: We have developed a novel human facial tracking system that operates in real time at a video frame rate without needing any special hardware. The approach is based on the use of Lie algebra, and uses three-dimensional feature points on the targeted human face. It is assumed that the roughly estimated facial model (relative coordinates of the three-dimensional feature points) is known. First, the initial feature positions of the face are determined using a model fitting technique. Then, the tracking is operated by the following sequence: (1) capture the new video frame and render feature points to the image plane; (2) search for new positions of the feature points on the image plane; (3) get the Euclidean matrix from the moving vector and the three-dimensional information for the points; and (4) rotate and translate the feature points by using the Euclidean matrix, and render the new points on the image plane. The key algorithm of this tracker is to estimate the Euclidean matrix by using a least square technique based on Lie algebra. The resulting tracker performed very well on the task of tracking a human face.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_12_1733/_p
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@ARTICLE{e84-d_12_1733,
author={Akira INOUE, Tom DRUMMOND, Roberto CIPOLLA, },
journal={IEICE TRANSACTIONS on Information},
title={Real Time Feature-Based Facial Tracking Using Lie Algebras},
year={2001},
volume={E84-D},
number={12},
pages={1733-1738},
abstract={We have developed a novel human facial tracking system that operates in real time at a video frame rate without needing any special hardware. The approach is based on the use of Lie algebra, and uses three-dimensional feature points on the targeted human face. It is assumed that the roughly estimated facial model (relative coordinates of the three-dimensional feature points) is known. First, the initial feature positions of the face are determined using a model fitting technique. Then, the tracking is operated by the following sequence: (1) capture the new video frame and render feature points to the image plane; (2) search for new positions of the feature points on the image plane; (3) get the Euclidean matrix from the moving vector and the three-dimensional information for the points; and (4) rotate and translate the feature points by using the Euclidean matrix, and render the new points on the image plane. The key algorithm of this tracker is to estimate the Euclidean matrix by using a least square technique based on Lie algebra. The resulting tracker performed very well on the task of tracking a human face.},
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - Real Time Feature-Based Facial Tracking Using Lie Algebras
T2 - IEICE TRANSACTIONS on Information
SP - 1733
EP - 1738
AU - Akira INOUE
AU - Tom DRUMMOND
AU - Roberto CIPOLLA
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2001
AB - We have developed a novel human facial tracking system that operates in real time at a video frame rate without needing any special hardware. The approach is based on the use of Lie algebra, and uses three-dimensional feature points on the targeted human face. It is assumed that the roughly estimated facial model (relative coordinates of the three-dimensional feature points) is known. First, the initial feature positions of the face are determined using a model fitting technique. Then, the tracking is operated by the following sequence: (1) capture the new video frame and render feature points to the image plane; (2) search for new positions of the feature points on the image plane; (3) get the Euclidean matrix from the moving vector and the three-dimensional information for the points; and (4) rotate and translate the feature points by using the Euclidean matrix, and render the new points on the image plane. The key algorithm of this tracker is to estimate the Euclidean matrix by using a least square technique based on Lie algebra. The resulting tracker performed very well on the task of tracking a human face.
ER -