Context-aware Risk Degree Prediction for Smartphone Zombies

Erwin Wu, Chen-Chieh Liao, Ruofan Liu, Hideki Koike

Abstract: Using smartphones while walking is becoming a social problem. Recent works try to support this issue by different warning systems. However, most only focus on detecting obstacles, without considering the risk to the user. In this paper, we propose a deep learning-based context-aware risk prediction system using a built-in camera on smartphones, aiming to notify ”smombies” by a risk-degree based algorithm. The proposed system both estimates the risk degree of a potential obstacle and the user’s status, which can also be used for distracted driving or visually impaired people.