RESEARCH FOR CORRECTION OF PERSON IDENTIFICATION USING OBJECT TRACKING TECHNOLOGY

Abstract

 In Japan, taking the opportunity of the proposal of Society 5.0, the introduction of state-of-the-art technologies, such as IoT and AI, has been being examined. In particular, at construction sites, such technologies are expected to greatly contribute to an improvement in the productivity and development of safety management. A development of technology for managing the positions and conditions of workers to decrease accidents of minor collisions or falls has been attracting growing interest. Thus, paying attention to the safety management of construction sites, the authors have proposed the some methods of person identification by deep learning focusing on patterns pasted on the workers’ helmets. In the existing researches, however, there was a problem that the same person was not correctly identified successively between frames when erroneous identification occurs due to the difference in the distance from the camera or the way the pattern was reflected. In this research, a new correction method is devised based on tracking of the helmets and improved the person identification method. As a result of conducting demonstration experiments, knowledge was obtained that this correction method is effective.