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.
