Reconstruction of facial shape from freehand multi-viewpoint snapshots

Seiji Suzuki, Hideo Saito, Masaaki Mochimaru

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

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.

元の言語English
ホスト出版物のタイトルAdvances in Visual Computing - 5th International Symposium, ISVC 2009, Proceedings
ページ641-650
ページ数10
エディションPART 2
DOI
出版物ステータスPublished - 2009
イベント5th International Symposium on Advances in Visual Computing, ISVC 2009 - Las Vegas, NV, United States
継続期間: 2009 11 302009 12 2

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 2
5876 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

Other

Other5th International Symposium on Advances in Visual Computing, ISVC 2009
United States
Las Vegas, NV
期間09/11/3009/12/2

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Suzuki, S., Saito, H., & Mochimaru, M. (2009). Reconstruction of facial shape from freehand multi-viewpoint snapshots. : Advances in Visual Computing - 5th International Symposium, ISVC 2009, Proceedings (PART 2 版, pp. 641-650). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 5876 LNCS, 番号 PART 2). https://doi.org/10.1007/978-3-642-10520-3_61