Rafael Mosberger and Henrik Andreasson
Estimating the 3D Position of Humans wearing a Reflective Vest using a Single Camera System
Proceedings of the International Conference on Field and Service Robotics (FSR), July 2012.

This paper presents a novel possible solution for people detection and estimation of their 3D position in challenging shared environments. Addressing safety critical applications in industrial environments, we make the basic assumption that people wear reflective vests. In order to detect these vests and to discriminate them from other reflective material, we propose an approach based on a single camera equipped with an IR flash. The camera acquires pairs of images, one with and one without IR flash, in short succession. The images forming a pair are then related to each other through feature tracking, which allows to discard features for which the relative intensity difference is small and which are thus not believed to belong to a reflective vest. Next, the local neighbourhood of the remaining features is further analysed. First, a Random Forest classifier is used to discriminate between features caused by a reflective vest and features caused by some other reflective materials. Second, the distance between the camera and the vest features is estimated using a Random Forest regressor. The proposed system was evaluated in one indoor and two challenging outdoor scenarios. Our results indicate very good classification performance and remarkably accurate distance estimation especially in combination with the SURF descriptor, even under direct exposure to sunlight.

Keywords: People Detection, Industrial Safety, Reflective Vest Detection
Paper: PDF (0.25 MB)
  AUTHOR = {Mosberger, Rafael and Andreasson, Henrik},
  TITLE = {Estimating the 3D position of humans wearing a reflective vest using a single camera system},
  BOOKTITLE = {Proceedings of the International Conference on Field and Service Robotics (FSR)},
  YEAR = {2012},