Automatic Helmet Detection and Gate Opening using YOLOv3

With an increase in the population and improving lifestyle, the demand for transport has increased tremendously. An increase in the number of vehicles increases the risk of accidents. Automatic helmet detection plays an important role in preventing people from breaking the rule of “Helmet Wearing”. Many companies/institutions have, therefore, imposed a rule which says “No entry without helmet”. In this paper, an approach is proposed for automatic gate opening for two-wheeler riders wearing helmets. In this proposed approach twowheeler riders from surveillance videos are detected and then it determines whether the twowheeler rider is wearing a helmet or not. Transfer learning has been implemented using Yolo (You only look once) to detect the two-wheeler riders with and without helmets in real-time with the help of surveillance cameras to determine whether the gate needs to be opened or not.