Omnidirectional vision for mobile robot human body detection and localization

Abstract

Human body detection and localization is an essential capability of an autonomous mobile robot which works in the human-robot interaction (HRI) environments. However, due to field of view (FOV) limitations, it is hard to detect all human bodies around a mobile robot by using a conventional camera, and distances between robots and human bodies are also difficult to estimate. In this paper, we propose a novel omnidirectional visual system to locate positions of human bodies for an autonomous mobile robot. Firstly, a handy fitting shape based method (FSM) is presented to remap a omnidirectional image to a bird's eye view image. A new bird's eye view image segmentation algorithm, which is inspired by image pyramids, is used to split obstacle objects and ground plane. Secondly, a shape-based human body detector is implemented in unwrapped omnidirectional images to locate regions of human bodies. These human body detection results are combined with bird's eye view image segmentation to distinguish human bodies from other obstacle objects. Experiments show that our system performs well in human-robot interaction environments.