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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.

- Publication
- IEICE TRANSACTIONS on Information Vol.E84-D No.12 pp.1733-1738

- Publication Date
- 2001/12/01

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- Special Section LETTER (Special Issue on Machine Vision Applications)

- Category

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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 -