Human Interface Research

Research Topics

• Facial Expression Communication
• Gesture Recognition

  Facial Expression Communication

  In this paper, the facial expression is mainly focused to achieve the smooth human tele-communications. In human communication society, the ``gestures'' and ``facial expressions'' has been considered as the most significant factors in usual communications. At first, to realize the facial expression communication system in real time, we proposed the facial expression space (FES) with PCA analysis, which can drastically reduce the dimension of images to FES without any consideration of facial features, such as eye blow, etc. Secondly, a correspondence technique between each personal facial expression spaces has been proposed with the affine transformation. Finally, real time facial expression transportation system has been developed, which transport the facial expression, but not the image itself. This final system leads to synthesize the same facial expressions in another persons, further more in cartoon characters. The experimental results show the validity of these criteria.
  
  Fig: Facial Expression Transportation
  
  Fig: Real-Time Facial Expression Trans.

  Publications

  • Kohtaro Ohba, Takehito Tsukada, Tetsuo Kotoku and Kazuo Tanie,

    Facial Expression Space for Smooth Tele-Communications PS PDF,

    Proc. Third IEEE International Conference on Automatic Face and Gesture Recognition (FG'98),

    pp. 378-383,

    14-16, April, 1998, Nara(Japna),

  • Kohtaro Ohba, Guillaume Clary, Takehito Tsukada, Tetsuo Kotoku and Kazuo Tanie,

    Facial Expression Communication with FES PS PDF,

    Proc. 14 th International Conference on Pattern Recognition (ICPR'98),

    pp. 1376-1378,

    16-20, Aug., 1998, Brisbane(Australia),

  • Kohtaro Ohba, Guillaume Clary, Yoshihito Hiratsuka, Takehito Tsukada,

    Tetsuo Kotoku and Kazuo Tanie,

    Gesture and Facial Expression on Tele-Robotics PS PDF,

    Proc. IEEE/RSJ International Conference on Intelligent Robots and System (IROS'98),

    pp. 378-383,

    13-17, Oct., 1998, Victoria(Canada),

  Gesture Recognition

  This paper describes a real-time system to classify several human motions with the principle component analysis, i.e. the eigen space method. First, to solve the drawback of original eigen space technique, such as background noise, silhouette images has been derived instead of original images. Secondly, a curvature in eigen space has been projected from a sequence of silhouette images. Finally, correspondence technique between dictionary and input curvatures have been discussed to classify human motions. Experimental results show the validity of this proposed method.
  
  Fig: Making a curvature in eigen space.
  
  Fig: Gesture identification in eigen space.

  Publications

  • Yoshihito Hiratsuka, Kohtaro Ohba, Shinya Kajikawa and Hikaru Inooka,

    Real-Time Human Motion Classification with Visual Information,

    Trans. Japanese Soc. Mech. Eng., (will be published)