Augmenting User Identification with WiFi Based Gesture Recognition

Abstract

Over the last few years, researchers have proposed several WiFi based gesture recognition systems that can recognize predefined gestures performed by users at runtime. As most environments are inhabited by multiple users, the true potential of WiFi based gesture recognition can be unleashed only when each user can independently define the actions that the system should take when the user performs a certain predefined gesture. To enable this, a gesture recognition system should not only be able to recognize any given predefined gesture, but should also be able to identify the user that performed it. Unfortunately, none of the prior WiFi based gesture recognition systems can identify the user performing the gesture. In this paper, we propose WiID, a WiFi and gesture based user identification system that can identify the user as soon as he/she performs a predefined gesture at runtime. WiID integrates with the WiFi based gesture recognition systems as an add-on module whose sole objective is to identify the users that perform the predefined gestures. The design of WiID is based on our novel result which states that the timeseries of the frequencies that appear in WiFi channel's frequency response while performing a given gesture are different in the samples of that gesture performed by different users, and are similar in the samples of that gesture performed by the same user. We implemented and extensively evaluated WiID in a variety of environments using a comprehensive data set comprising over 25,000 gesture samples.