Affective science and engineering
visual material perception
CNN (convolutional neural network)
Vision Society of Japan
Main research topics
I am interested in “visual material perception,” or how humans visually perceive the surface texture and material of objects. Our colleagues and I do research combining psychophysical methods, image analysis, machine learning, and pupil measurement. Mainly, I focus on how the human visual system uses cues from graphical images to quickly and accurately estimate surface properties and identify materials. We aim to apply the knowledge we have gained from human cognitive and behavioral characteristics to technologies that enable faster, more accurate, and less costly measurement and representation of texture.
Recently, I am also interested in the research and development of mobility (≒autonomous mobile robots) that will play an active role in the future era of smart cities. I am working on this as one of my projects. In the recent COVID-19 disaster, mobility has accelerated the logistics, food and beverage, and security industries to avoid human-to-human contact. I believe that there will be more and more opportunities for us to be involved with mobility in our daily lives, both indoors and outdoors. Thus, our goal is to achieve mobility that allows us to interact with people more safely, securely, and comfortably than ever before by focusing on human cognitive and behavioral characteristics.
Tamura, H., Prokott K. E., & Fleming, R. W. (2022). Distinguishing mirror from glass: A “big data” approach to material perception, Journal of Vision, 22(4): 4, 1-22, https://doi.org/10.1167/jov.22.4.4.
Tamura, H., Higashi, H., & Nakauchi, S. (2018). Dynamic Visual Cues for Differentiating Mirror and Glass, Scientific Reports, 8, 8403. https://doi.org/10.1038/s41598-018-26720-x