Chen Liang
Tsinghua University, Beijing, Beijing, China
In this paper, we propose Auth+Track, a novel authentication model that aims to reduce redundant authentication in everyday smartphone usage. By sparse authentication and continuous tracking of user's status, Auth+Track eliminates the "gap" authentication between fragmented sessions and enables "Authentication Free when User is Around". To instantiate Auth+Track model, we present PanoTrack, a valid implementation that integrates body and near field hand information for user tracking. We install a fisheye camera on the top of the phone to achieve panoramic vision that can capture both user's body and on-screen hand. Based on the captured video stream, we develops an algorithm pipeline to extract all the key features for user tracking, including body keypoints and their temporal and spacial association, near field hand status and features for user identity assignment. By analyzing system performance and user experience in real-life scenarios, we demonstrate that our system outperforms existing solutions.
https://doi.org/10.1145/3411764.3445624
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)