Computer Vision and Human Computer Interaction
Computer vision and machine learning techniques have achieved significant advances in recent years and attracting broad attention from a variety of application areas. However, there is still a gap towards the level required for daily-life usage in many aspects such as recognition robustness and diversity of recognition tasks, even with the state-of-the-art image recognition algorithms. In order to apply image recognition techniques to daily-life applications, we believe it is required to develop recognition systems from a holistic perspective including human-machine interaction. Mechanisms to infer the actual user- and task-specific demands and to adaptively improve the recognition performance is a key step towards bridging the gap between generic and application-specific recognition systems. To achieve this goal, our research interests span multiple disciplines including both computer vision and human-computer interaction, and we conduct a wide spectrum of researches from basic methodologies to application systems.
- 2010: Ph. D. in Information Science and Technology, The University of Tokyo
- 2010: Project Research Associate, Institute of Industrial Science, The University of Tokyo
- 2014: Postdoctoral Researcher, Max Planck Institute for Informatics
- 2016: Associate Professor, Graduate School for Information Science and Technology, Osaka University
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