Human Pose Estimation from Volume Data and Topological Graph Database

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Human Pose Estimation from Volume Data and Topological Graph Database

Tanaka, Hidenori / Nakazawa, Atsushi / Takemura, Haruo

This paper proposes a novel volume-based motion capture method using a bottom-up analysis of volume data and an example topology database of the human body. By using a two-step graph matching algorithm with many example topological graphs corresponding to postures that a human body can take, the proposed method does not require any initial parameters or iterative convergence processes, and it can solve the changing topology problem of the human body. First, three-dimensional curved lines (skeleton) are extracted from the captured volume data using the thinning process. The skeleton is then converted into an attributed graph. By using a graph matching algorithm with a large amount of example data, we can identify the body parts from each curved line in the skeleton. The proposed method is evaluated using several video sequences of a single person and multiple people, and we can confirm the validity of our approach.

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Document information

Title :

Human Pose Estimation from Volume Data and Topological Graph Database

Contributors:

Yagi, Yasushi (editor) / Kang, Sing Bing (editor) / Kweon, In So (editor) / Zha, Hongbin (editor) / Tanaka, Hidenori (author) / Nakazawa, Atsushi (author) / Takemura, Haruo (author)

Conference:

Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007

Published in:

Computer Vision – ACCV 2007 ; Chapter : 58 ; 618-627

Lecture Notes in Computer Science ; 4843

Publication date :

2007-01-01

Size :

10 pages

ISBN :

978-3-540-76386-4 , 978-3-540-76385-7

ISSN :