Novel Active Vision-Based Visual Threat Cue for Autonomous Navigation Tasks

摘要

This paper deals with a novel vision-based motion cue called the Visual Threat Cue (VTC), suitable for autonomous navigation tasks such as collision avoidance and maintenance of clearance. The VTC is atime-basedscalar parameter that provides some measure for arelative change in rangeas well asclearancebetween a 3D surface and amovingobserver. It is independent of the 3D environment around the observer and needs almost noa prioriknowledge about it. A practical method to extract the VTC from a sequence of images of 3D textured surfaces is also presented. It is based on the extraction of a global image dissimilarity measure called the Image Quality Measure (IQM), which is extracted directly from the raw data of the gray level images. Based on the relative variations of the measured IQM, the VTC is extracted. Several experimental results are also presented.