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Finding Kinematic Structure in Time Series Volume Data
Mukasa, Tomoyuki (Kyoto University. Graduate School of Informatics)
Nobuhara, Shohei (Kyoto University. Graduate School of Informatics)
Maki, Atsuto (Kyoto University. Graduate School of Informatics)
Matsuyama, Takashi (Kyoto University. Graduate School of Informatics)

Data: 2009
Resum: This paper presents 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. The only assumption we make is that human body can be approximated by an articulated body with certain numbers of end-points and branches. We demonstrate the efficacy of the proposed scheme through some experiments.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Captura del moviment basada en la visió ; Video i Anàlisi de Seqüència d'imatges ; Gràfic de Reeb ; Seguiment i anàlisi de moviments ; Captura del movimiento basada en la visión ; Video y Análisis de Secuencia de imágenes ; Gráfico de Reeb ; Seguimiento y análisis de movimientos ; Vision-Based Motion Capture ; Video and Image Sequence Analysis ; Reeb graph ; Motion Tracking and Analysis
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 7 n. 4 (2009) p. 62-72, ISSN 1577-5097

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