Face reconstruction using a small set of feature points

Bon Woo Hwang; Volker Blanz; Thomas Vetter; Seong Whan Lee

doi:10.1007/3-540-45482-9_30

Face reconstruction using a small set of feature points

Bon Woo Hwang, Volker Blanz, Thomas Vetter, Seong Whan Lee

Department of Brain and Cognitive Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

This paper proposes a method for face reconstruction that makes use of only a small set of feature points. Faces can be modeled by forming linear combinations of prototypes of shape and texture information. With the shape and texture information at the feature points alone, we can achieve only an approximation to the deformation required. In such an under-determined condition, we find an optimal solution using a simple least square minimization method. As experimental results, we show well-reconstructed 2D faces even from a small number of feature points.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
Pages	308-315
Number of pages	8
Volume	1811
ISBN (Print)	3540675604, 9783540675600
DOIs	https://doi.org/10.1007/3-540-45482-9_30
Publication status	Published - 2000
Event	1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000 - Seoul, Korea, Republic of Duration: 2000 May 15 → 2000 May 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1811
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000
Country	Korea, Republic of
City	Seoul
Period	00/5/15 → 00/5/17

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/3-540-45482-9_30

Fingerprint Dive into the research topics of 'Face reconstruction using a small set of feature points'. Together they form a unique fingerprint.

Cite this

Hwang, B. W., Blanz, V., Vetter, T., & Lee, S. W. (2000). Face reconstruction using a small set of feature points. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1811, pp. 308-315). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1811). Springer Verlag. https://doi.org/10.1007/3-540-45482-9_30

Face reconstruction using a small set of feature points. / Hwang, Bon Woo; Blanz, Volker; Vetter, Thomas; Lee, Seong Whan.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1811 Springer Verlag, 2000. p. 308-315 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1811).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hwang, BW, Blanz, V, Vetter, T & Lee, SW 2000, Face reconstruction using a small set of feature points. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 1811, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1811, Springer Verlag, pp. 308-315, 1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000, Seoul, Korea, Republic of, 00/5/15. https://doi.org/10.1007/3-540-45482-9_30

Hwang BW, Blanz V, Vetter T, Lee SW. Face reconstruction using a small set of feature points. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1811. Springer Verlag. 2000. p. 308-315. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-45482-9_30

Hwang, Bon Woo ; Blanz, Volker ; Vetter, Thomas ; Lee, Seong Whan. / Face reconstruction using a small set of feature points. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1811 Springer Verlag, 2000. pp. 308-315 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{41d23bc76dd449c1956b381540c0266a,

title = "Face reconstruction using a small set of feature points",

abstract = "This paper proposes a method for face reconstruction that makes use of only a small set of feature points. Faces can be modeled by forming linear combinations of prototypes of shape and texture information. With the shape and texture information at the feature points alone, we can achieve only an approximation to the deformation required. In such an under-determined condition, we find an optimal solution using a simple least square minimization method. As experimental results, we show well-reconstructed 2D faces even from a small number of feature points.",

author = "Hwang, {Bon Woo} and Volker Blanz and Thomas Vetter and Lee, {Seong Whan}",

year = "2000",

doi = "10.1007/3-540-45482-9_30",

language = "English",

isbn = "3540675604",

volume = "1811",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "308--315",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

note = "1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000 ; Conference date: 15-05-2000 Through 17-05-2000",

}

TY - GEN

T1 - Face reconstruction using a small set of feature points

AU - Hwang, Bon Woo

AU - Blanz, Volker

AU - Vetter, Thomas

AU - Lee, Seong Whan

PY - 2000

Y1 - 2000

N2 - This paper proposes a method for face reconstruction that makes use of only a small set of feature points. Faces can be modeled by forming linear combinations of prototypes of shape and texture information. With the shape and texture information at the feature points alone, we can achieve only an approximation to the deformation required. In such an under-determined condition, we find an optimal solution using a simple least square minimization method. As experimental results, we show well-reconstructed 2D faces even from a small number of feature points.

AB - This paper proposes a method for face reconstruction that makes use of only a small set of feature points. Faces can be modeled by forming linear combinations of prototypes of shape and texture information. With the shape and texture information at the feature points alone, we can achieve only an approximation to the deformation required. In such an under-determined condition, we find an optimal solution using a simple least square minimization method. As experimental results, we show well-reconstructed 2D faces even from a small number of feature points.

UR - http://www.scopus.com/inward/record.url?scp=33744959572&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33744959572&partnerID=8YFLogxK

U2 - 10.1007/3-540-45482-9_30

DO - 10.1007/3-540-45482-9_30

M3 - Conference contribution

AN - SCOPUS:33744959572

SN - 3540675604

SN - 9783540675600

VL - 1811

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 308

EP - 315

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer Verlag

T2 - 1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000

Y2 - 15 May 2000 through 17 May 2000

ER -