User's Height Estimation based on Acceleration from Smartphone Sensors
Yusuke Sato, Saneyasu Yamaguchi, Takeshi Kamiyama, Akira Fukuda, Masato Oguchi · 2019
The recent advance of machine learning enabled a variety of estimation data from sensors. In this study, we investigate estimation of the heights of the users of smartphones from the sensed data for the next step of the studies of estimation based on the machine learning. We propose a method for estimating the two-classed height, which is tall or short, by the linear regression. Our evaluation shows that the proposed method estimated the height class with 92% accuracy in case of persons whose heights are far from the median height.