Omnidirectional vision for mobile robot human body detection and localization

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.