Cho, J., Hwang, I. & Oh, S. Pattern Anal Applic (2016) 19: 251. doi:10.1007/s10044-015-0460-8
With various sensors in a smartphone, it is now possible to obtain information about a user and her surroundings, such as the location and the activity of the smartphone user, and the obtained context information is being used to provide new services to the users. In this paper, we propose VibePhone, which uses a built-in vibrator and accelerometer, for efficiently recognizing the type of surfaces contacted by a smartphone, enabling the sense of touch to smartphones. In particular, this paper focuses on developing a succinct set of features that are useful for recognizing surface types for reducing computation and memory requirements, which will in turn reduce the power consumption of the device. For humans and animals, the sense of touch, which is obtained from the texture of an object by scrubbing its surface, is fundamental for both recognizing and learning the properties of objects. Since a smartphone cannot physically scrub the contacting surface, we emulate the touch by generating vibrations and analyzing accelerometer readings. While the recognition of the object type by vibration alone is an extremely difficult task, even for a human, we demonstrate that it is possible to distinguish object types into broad categories where a phone is usually placed. For efficiency, VibePhone uses only a small subset of the most informative features of accelerometer readings using feature selection and reduces the computation time by 92 % using only 15 % of features, while maintaining performance. We believe that our analysis of vibrations about contacted surfaces can provide an important insight for the haptic perception in future smartphones, enabling new experiences to the users.