A New Approach using Modified Hausdorff Distances with EigenFace for Human Face Recognition

Kwan Ho Lin; Kin Man Lam; Wan Chi Siu

A New Approach using Modified Hausdorff Distances with EigenFace for Human Face Recognition

Kwan Ho Lin, Kin Man Lam, Wan Chi Siu

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

5 Citations (Scopus)

Abstract

Hausdorff distance is an efficient measure of the similarity of two point sets. In this paper, we propose two new spatially weighted Hausdorff distance measures for human face recognition, namely, spatially eigen-weighted Hausdorff distance (SEWHD) and spatially eigen-weighted 'doubly' Hausdorff distance (SEW2HD). These new Hausdorff distances incorporate the information about the location of important facial features so that distances at those regions will be emphasized. The weighting function used in the Hausdorff distance measure is based on an eigenface, which has a large value at locations of important facial features and can reflect the face structure more effectively. Experimental results based on a combination of the ORL, MIT, and Yale face databases show that SEW2HD can achieve recognition rates of 83%, 90% and 92% for the first one, the first three and the first five likely matched faces, respectively, while the corresponding recognition rates of SEWHD are 80%, 83% and 88%, respectively.

Original language	English
Title of host publication	Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002
Pages	980-984
Number of pages	5
Publication status	Published - 1 Dec 2002
Event	Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARC 2002 - Singapore, Singapore Duration: 2 Dec 2002 → 5 Dec 2002

Conference

Conference	Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARC 2002
Country/Territory	Singapore
City	Singapore
Period	2/12/02 → 5/12/02

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{551919f468664925ad514fea06d25607,

title = "A New Approach using Modified Hausdorff Distances with EigenFace for Human Face Recognition",

abstract = "Hausdorff distance is an efficient measure of the similarity of two point sets. In this paper, we propose two new spatially weighted Hausdorff distance measures for human face recognition, namely, spatially eigen-weighted Hausdorff distance (SEWHD) and spatially eigen-weighted 'doubly' Hausdorff distance (SEW2HD). These new Hausdorff distances incorporate the information about the location of important facial features so that distances at those regions will be emphasized. The weighting function used in the Hausdorff distance measure is based on an eigenface, which has a large value at locations of important facial features and can reflect the face structure more effectively. Experimental results based on a combination of the ORL, MIT, and Yale face databases show that SEW2HD can achieve recognition rates of 83%, 90% and 92% for the first one, the first three and the first five likely matched faces, respectively, while the corresponding recognition rates of SEWHD are 80%, 83% and 88%, respectively.",

author = "Lin, {Kwan Ho} and Lam, {Kin Man} and Siu, {Wan Chi}",

year = "2002",

month = dec,

day = "1",

language = "English",

isbn = "9810474806",

pages = "980--984",

booktitle = "Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002",

note = "Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARC 2002 ; Conference date: 02-12-2002 Through 05-12-2002",

}

Lin, KH, Lam, KM & Siu, WC 2002, A New Approach using Modified Hausdorff Distances with EigenFace for Human Face Recognition. in Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002. pp. 980-984, Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARC 2002, Singapore, Singapore, 2/12/02.

A New Approach using Modified Hausdorff Distances with EigenFace for Human Face Recognition. / Lin, Kwan Ho; Lam, Kin Man; Siu, Wan Chi.
Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002. 2002. p. 980-984.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - A New Approach using Modified Hausdorff Distances with EigenFace for Human Face Recognition

AU - Lin, Kwan Ho

AU - Lam, Kin Man

AU - Siu, Wan Chi

PY - 2002/12/1

Y1 - 2002/12/1

N2 - Hausdorff distance is an efficient measure of the similarity of two point sets. In this paper, we propose two new spatially weighted Hausdorff distance measures for human face recognition, namely, spatially eigen-weighted Hausdorff distance (SEWHD) and spatially eigen-weighted 'doubly' Hausdorff distance (SEW2HD). These new Hausdorff distances incorporate the information about the location of important facial features so that distances at those regions will be emphasized. The weighting function used in the Hausdorff distance measure is based on an eigenface, which has a large value at locations of important facial features and can reflect the face structure more effectively. Experimental results based on a combination of the ORL, MIT, and Yale face databases show that SEW2HD can achieve recognition rates of 83%, 90% and 92% for the first one, the first three and the first five likely matched faces, respectively, while the corresponding recognition rates of SEWHD are 80%, 83% and 88%, respectively.

AB - Hausdorff distance is an efficient measure of the similarity of two point sets. In this paper, we propose two new spatially weighted Hausdorff distance measures for human face recognition, namely, spatially eigen-weighted Hausdorff distance (SEWHD) and spatially eigen-weighted 'doubly' Hausdorff distance (SEW2HD). These new Hausdorff distances incorporate the information about the location of important facial features so that distances at those regions will be emphasized. The weighting function used in the Hausdorff distance measure is based on an eigenface, which has a large value at locations of important facial features and can reflect the face structure more effectively. Experimental results based on a combination of the ORL, MIT, and Yale face databases show that SEW2HD can achieve recognition rates of 83%, 90% and 92% for the first one, the first three and the first five likely matched faces, respectively, while the corresponding recognition rates of SEWHD are 80%, 83% and 88%, respectively.

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BT - Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARCV 2002

T2 - Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision, ICARC 2002

Y2 - 2 December 2002 through 5 December 2002

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A New Approach using Modified Hausdorff Distances with EigenFace for Human Face Recognition

Abstract

Conference

ASJC Scopus subject areas

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