An Image-Based Visual-Motion-Cue for Autonomous Navigatio

Abstract

This paper presents a novel time-based visual motion cue called the Hybrid Visual Threat Cue (HVTC) that provides some measure for a change in relative range as well as absolute clearances, between a 3D surface and a moving observer. It is shown that the HVTC is a linear combination of Time-To-Contact (TTC), visual looming and the Visual Threat Cue (VTC). The visual field associated with the HVTC can be used to demarcate the regions around a moving observer into safe and danger zones of varying degree, which may be suitable for autonomous navigation tasks. The HVTC is independent of the 3D environment and needs almost no a-priori information about it. It is rotation independent, and is measured in ~time/sup -1/\ units Several approaches to extract the HVTC, are suggested. Also a practical method to extract it from a sequence of images of a 3D textured surface obtained by a visually fixating, fixed-focus monocular camera in motion is presented. This approach of extracting the HVTC is independent of the type of 3D surface texture and needs no optical flow information, 3D reconstruction, segmentation, feature tracking.