TALK    Challenges on shape acquisition of moving object

Date released: August 17, 2012


  •  TALK    Challenges on shape acquisition of moving object
  • Date & Time:

    Friday, August 17, 2012; 12:00 PM

  • Abstract:

    In this talk, I will introduce an overview of my research projects on 3D shape acquisition of moving object. The talk mainly focuses on two parts, the first one is about our 3D shape acquisition technique using projector and camera system and the second is entire shape acquisition using multi-view pro-cam system. I also briefly cover the following topics:

    -- Theory of shape from coplanarity technique
    -- Texture recovery method on pro-cam system
    -- Future plan on medical application of our scanner

    Those researches are jointly researched by Prof. Katushi Ikeuchi (Univ. of Tokyo), Prof. Ryo Furukawa (Hiroshima city Univ) and Prof. Ryusuke Sagawa (AIST).

  • Speaker:

    Prof. Hiroshi Kawasaki
    Kagoshima University

    Full professor of Department of Information and Biomedial Engineering at Kagoshima University, Japan. His current research focus is on a capturing technique of shape and texture of moving objects and it's rendering/VR/AR system. He received a Ph.D. degree from University of Tokyo, Japan, in 2003 (Advising professors were Prof. Katsushi Ikeuchi and Prof. Masao Sakauchi). He started working at Kagoshima university in 2010. Prior to Kagoshima university, he worked at Saitama university. He also researched at INRIA Rhone Alpes with Peter Sturm in 2009 and Microsoft Research Redmond with Sing Bing Kang and Richard Szeliski in 2000. He has published over 100 research papers including ICCV, CVPR, IJCV, 3DIM, Eurographics and MVA in computer vision and computer graphics and won several awards including Songde Ma Outstanding Paper Award (best paper for ACCV) in 2007, best paper award on PSIVT in 2009 and Nagao Prize (best paper on MIRU) in 2011. He is a member of IPSJ, IEICE, and IEEE.

  • External Link:

    http://www.ibe.kagoshima-u.ac.jp/~cgv/

  • Research Area:

    Computer Vision