Reconstruction of facial shape from freehand multi-viewpoint snapshots

Seiji Suzuki, Hideo Saito, Masaaki Mochimaru

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We propose a method that can reconstruct both a 3D facial shape and camera poses from freehand multi-viewpoint snapshots. This method is based on Active Shape Model (ASM) using a facial shape database. Most ASM methods require an image in which the camera pose is known, but our method does not require this information. First, we choose an initial shape by selecting the model from the database which is most suitable to input images. Then, we improve the model by morphing it to fit the input images. Next, we estimate the camera poses using the morphed model. Finally we repeat the process, improving both the facial shape and the camera poses until the error between the input images and the computed result is minimized. Through experimentation, we show that our method reconstructs the facial shape within 3.5 mm of the ground truth.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages641-650
Number of pages10
Volume5876 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2009
Event5th International Symposium on Advances in Visual Computing, ISVC 2009 - Las Vegas, NV, United States
Duration: 2009 Nov 302009 Dec 2

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5876 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th International Symposium on Advances in Visual Computing, ISVC 2009
CountryUnited States
CityLas Vegas, NV
Period09/11/3009/12/2

Fingerprint

Snapshot
Camera
Cameras
Active Shape Model
Morphing
Experimentation
Choose
Model
Estimate

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Suzuki, S., Saito, H., & Mochimaru, M. (2009). Reconstruction of facial shape from freehand multi-viewpoint snapshots. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 5876 LNCS, pp. 641-650). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5876 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-10520-3_61

Reconstruction of facial shape from freehand multi-viewpoint snapshots. / Suzuki, Seiji; Saito, Hideo; Mochimaru, Masaaki.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5876 LNCS PART 2. ed. 2009. p. 641-650 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5876 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suzuki, S, Saito, H & Mochimaru, M 2009, Reconstruction of facial shape from freehand multi-viewpoint snapshots. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 edn, vol. 5876 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5876 LNCS, pp. 641-650, 5th International Symposium on Advances in Visual Computing, ISVC 2009, Las Vegas, NV, United States, 09/11/30. https://doi.org/10.1007/978-3-642-10520-3_61
Suzuki S, Saito H, Mochimaru M. Reconstruction of facial shape from freehand multi-viewpoint snapshots. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 ed. Vol. 5876 LNCS. 2009. p. 641-650. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-642-10520-3_61
Suzuki, Seiji ; Saito, Hideo ; Mochimaru, Masaaki. / Reconstruction of facial shape from freehand multi-viewpoint snapshots. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5876 LNCS PART 2. ed. 2009. pp. 641-650 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
@inproceedings{53c704985e2743e9add6ee0bc42ae6fa,
title = "Reconstruction of facial shape from freehand multi-viewpoint snapshots",
abstract = "We propose a method that can reconstruct both a 3D facial shape and camera poses from freehand multi-viewpoint snapshots. This method is based on Active Shape Model (ASM) using a facial shape database. Most ASM methods require an image in which the camera pose is known, but our method does not require this information. First, we choose an initial shape by selecting the model from the database which is most suitable to input images. Then, we improve the model by morphing it to fit the input images. Next, we estimate the camera poses using the morphed model. Finally we repeat the process, improving both the facial shape and the camera poses until the error between the input images and the computed result is minimized. Through experimentation, we show that our method reconstructs the facial shape within 3.5 mm of the ground truth.",
author = "Seiji Suzuki and Hideo Saito and Masaaki Mochimaru",
year = "2009",
doi = "10.1007/978-3-642-10520-3_61",
language = "English",
isbn = "364210519X",
volume = "5876 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "641--650",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
edition = "PART 2",

}

TY - GEN

T1 - Reconstruction of facial shape from freehand multi-viewpoint snapshots

AU - Suzuki, Seiji

AU - Saito, Hideo

AU - Mochimaru, Masaaki

PY - 2009

Y1 - 2009

N2 - We propose a method that can reconstruct both a 3D facial shape and camera poses from freehand multi-viewpoint snapshots. This method is based on Active Shape Model (ASM) using a facial shape database. Most ASM methods require an image in which the camera pose is known, but our method does not require this information. First, we choose an initial shape by selecting the model from the database which is most suitable to input images. Then, we improve the model by morphing it to fit the input images. Next, we estimate the camera poses using the morphed model. Finally we repeat the process, improving both the facial shape and the camera poses until the error between the input images and the computed result is minimized. Through experimentation, we show that our method reconstructs the facial shape within 3.5 mm of the ground truth.

AB - We propose a method that can reconstruct both a 3D facial shape and camera poses from freehand multi-viewpoint snapshots. This method is based on Active Shape Model (ASM) using a facial shape database. Most ASM methods require an image in which the camera pose is known, but our method does not require this information. First, we choose an initial shape by selecting the model from the database which is most suitable to input images. Then, we improve the model by morphing it to fit the input images. Next, we estimate the camera poses using the morphed model. Finally we repeat the process, improving both the facial shape and the camera poses until the error between the input images and the computed result is minimized. Through experimentation, we show that our method reconstructs the facial shape within 3.5 mm of the ground truth.

UR - http://www.scopus.com/inward/record.url?scp=72449141106&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=72449141106&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-10520-3_61

DO - 10.1007/978-3-642-10520-3_61

M3 - Conference contribution

AN - SCOPUS:72449141106

SN - 364210519X

SN - 9783642105197

VL - 5876 LNCS

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

SP - 641

EP - 650

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

ER -