Garuda: a deep learning based solution for capturing selfies safely

Abstract

Clicking selfies using mobile phones has become a trend in the past few years. It is documented that the thrill of clicking selfies at adventurous places has resulted in serious injuries and even death in some cases. To overcome this, we propose a system which can alert the user by detecting the level of danger in the background while capturing selfies. Our app is based on a deep Convolutional Neural Network (CNN). The prediction is performed as a 5 class classification problem with classes representing a different level of danger. Face detection and device orientation information are also used for robustness and lesser battery consumption.