Projects

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Quantifying Discussion by Using Camera as a Smart Sensor

Quantifying Discussion by Using Camera as a Smart Sensor

The emergence of various types of commercial cameras (compact, high resolution, high angle of view, high speed, high dynamic range, etc.) has contributed significantly to the understanding of human activities. By taking advantage of the characteristic of a high angle of view, we demonstrate a system that recognizes micro-behaviors while a small group discussion with a single 360 degree camera towards quantified meeting analysis.

CoALA: Confidence-Aware Learning Assistant

CoALA: Confidence-Aware Learning Assistant

Self-confidence plays an important role in improving the quality of knowledge. Undesirable situations such as confident incorrect and unconfident correct knowledge prevent learners from revising their knowledge because it is not always easy for them to perceive the situations. Therefore we propose a system that estimates self-confidence by sensors and gives feedback about which question should be reviewed carefully.

HyperMind: Intelligent Digital Textbook

HyperMind: Intelligent Digital Textbook

Although every learner has different preferences in reading, textbooks have traditionally been static. Reading experiences should become more immersive and interesting if textbooks behave differently for each learner. We propose vivid interactions optimized for the context of learning by combining a digital document and affective state recognition (e.g. interest, mental workload, and self-confidence) using smart sensors.

Wordometer: Reading Activity Tracker

Wordometer: Reading Activity Tracker

We propose a system tracking the number of read words by analyzing eye movements measured by JINS MEME (commercial electrooculography glasses). As people are encouraged to be physically fit by monitoring step counts, counting the number of words they read and giving feedback is a potential approach to helping them increase their daily reading volume.

Sensor-Based Mental States Estimation

Sensor-Based Mental States Estimation

Mental illness, especially depression is one of the most pressing concerns all over the world. We propose a system estimating mental states of a user from activity log derived from sensors. It uses the analogy of thermometer for the visualization. Everyone should have gone through hardships with fever, and they can understand how much tired by this format.