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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kami telah membangunkan sistem pengesanan muka manusia baru yang beroperasi dalam masa nyata pada kadar bingkai video tanpa memerlukan sebarang perkakasan khas. Pendekatan ini berdasarkan penggunaan algebra Lie, dan menggunakan titik ciri tiga dimensi pada wajah manusia yang disasarkan. Diandaikan bahawa model muka yang dianggarkan secara kasar (koordinat relatif bagi titik ciri tiga dimensi) diketahui. Pertama, kedudukan ciri awal muka ditentukan menggunakan teknik pemasangan model. Kemudian, penjejakan dikendalikan oleh urutan berikut: (1) menangkap bingkai video baharu dan menjadikan titik ciri pada satah imej; (2) mencari kedudukan baharu titik ciri pada satah imej; (3) dapatkan matriks Euclidean daripada vektor bergerak dan maklumat tiga dimensi untuk titik; dan (4) putar dan menterjemah titik ciri dengan menggunakan matriks Euclidean, dan menjadikan titik baharu pada satah imej. Algoritma utama penjejak ini adalah untuk menganggarkan matriks Euclidean dengan menggunakan teknik kuasa dua terkecil berdasarkan algebra Lie. Penjejak yang terhasil melakukan dengan sangat baik dalam tugas menjejak wajah manusia.
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Salinan
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
Salinan
@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},}
Salinan
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 -