A real-time pedestrian detection system for safety applications

Abstract

Nowadays, People are more distracted by their vulnerable devices, whenever they enter a cross road. As a result, a fatal accident or injury will occur. This motivated the need to implement a reliable pedestrian detection system. To optimize the system, a cross road scenario is considered where the driver is taking a right turn and a smart camera is used to capture consecutive pictures of the pedestrian. The consecutive frames are studied using Region Of Interest method and the Gaussian mixture model method. Once the detected pedestrian enters region of interest in less than 2 meters, a warning and automatic brake system is initiated to prevent the accident. Finally, the results of the proposed methods are compared based on the processing speed and performance rate of the Shape based detection technique (Wei Zhang, [12]). The performance rate was above 90% and processing speed was about 1 sec for the proposed methods.