SNOW DEPTH EVALUATION FROM HIGHWAY MONITORING CAMERA USING DEEP LEARNING

Abstract

Evaluation of snow cover condition is essential to manage the road condition such as snow removal on the roof of a building or on the road. In particular, evaluation of snow depth requires the use of expensive sensors such as lasers in addition to visual evaluation. Image processing techniques such as deep learning have improved in recent years, and many studies have been conducted to evaluate the snow cover state using images from surveillance cameras. In particular, in the surveillance images of the road surface and shoulders by wayside cameras, the location information is clear because the shoot-ing location is fixed, and the angle of view changes relatively little. In this research, an AI method was applied to the evaluation of the snow depth of the snow on the shoulder using a surveillance camera.