Robotics Vision <IS-international collaboration Lab>

Research Staff

  • Prof. Kenji Doya

    Prof.
    Takeo Kanade

  • Assist.Prof. Yang Wu

    Assist.Prof.
    Yang Wu

E-mail { yangwu }[at] rsc.naist.jp

Research Area

Assistive technology for disabled/older people

We focus on exploring computer vision possibilities for better enhancing robotics systems or wearable devices for better serving and helping disabled/older people, not just for safety purposes, but also for improving their quality of life and better engagement in the society. We start with helping blind people "see" the attitudes and emotions of people who they are talking with using wearable cameras. Future research will cover other practical needs of different groups of people.

First-person vision with wearable cameras and mobile computing

First-person vision lets computers/robots see what we see, in exactly the same viewpoints and potentially the same time spans, and therefore it may be a better way to understand human vision, interest, intension, and behavior. We use wearable cameras and light mobile computing devices (e.g. smartphones) to capture and process this data, and communicate with other resources. This research is expected to better solve many traditional computer vision problems including segmentation, detection, tracking and recognition, and also further many new applications.

Scalable visual recognition for dealing with large amounts of data

As the big data era comes, we are able to share and access to large amounts of data, and connect countless amounts of sensors and devices. For computer vision, the critical research of visual recognition also goes from small-scale restricted data to large-scale real-world problems. We work on a representative task called large-scale across-camera person re-identification (with many cameras and people) to support large-scale real video surveillance systems. At the same time, we also look into more general problems such as image categorization and object recognition for investigating generic scalable visual recognition models. The research is also beneficial for our research on first-person vision.

Key Features

As one of the first two international collaborative laboratories established in NAIST, this laboratory is different from any other research or collaborative lab that you can find in the Graduate School of Information Science. It is unique in:

Being led by Prof. Takeo Kanade and closely collaborating with Carnegie Mellon University

Gathering active and talented researchers with very diverse nationalities

Targeting innovative research with global and long-lasting impact

Effectively connecting NAIST researchers and international peers




Fig.1  Assistive technology for disabled/older people

Fig.1 Assistive technology for disabled/older people

Fig.2  First-person vision with wearable cameras and mobile computing

Fig.2 First-person vision with wearable cameras and mobile computing

Fig.3  Scalable visual recognition for dealing with large amounts of data

Fig.3 Scalable visual recognition for dealing with large amounts of data