Finding Articulated Body, AMDO 2016 (Conference Paper)

this is my 1st publication.

T. Mukasa, S. Nobuhara, A. Maki, and T. Matsuyama: Finding Articulated Body in Time-series Volume Data, The 4th International Conference on Articulated Motion and Deformable Objects (F. J. Perales and R. B. Fisher: AMDO 2006, LNCS 4069), pp.395-404, 2006.7(PDF)

Tomoyuki Mukasa, Shohei Nobuhara, Atsuto Maki, and Takashi Matsuyama: Finding Kinematic Structure in Time Series Volume Data, Electronic Letters on Computer Vision and Image Analysis 7(4) 62-72, 2009. (PDF)

概要：
多視点映像から復元された時系列ボクセルデータから対象の骨格構造と運動を同時に獲得する手法を提案した。
まず時系列ボクセルデータを測地距離の総和に基づくReeb graphの系列を得た。
次に、獲得されたReeb graphを基にその構造が時系列全体に対して同一のものとなるよう変形し、対象物体の骨格構造を獲得した。

Abstract:
A new scheme for acquiring 3D kinematic structure and motion from time series volume data.
Our basic strategy is to first represent the shape structure of the target in each frame by Reeb graph which we compute by using geodesic distance of target’s surface, and then estimate the kinematic structure of the target which is consistent with these shape structures.
Although the shape structures can be very different from frame to frame, we propose to derive a unique kinematic structure by way of clustering some nodes of graph, based on the fact that they are partly coherent to a certain extent of time series.
Once we acquire a unique kinematic structure, we fit it to other Reeb graphs in the remaining frames, and describe
the motion throughout the entire time series.