Trackability as a cue for potential obstacle identification and 3-D description

摘要

In many man-made environments, obstacles in the path of a mobile robot can be characterized asshallow, that is, they have relatively small extent in depth compared to the distance from the camera. We present a framework for segmenting shallow structures from their background over a sequence of images. Shallowness is first quantified asaffine describability. This is embedded in a tracking system within which hypothesized model structures undergo a cycle of prediction and model-matching. Structures emerge either as shallow or nonshallow based on theiraffine trackability. Two major contributions of this work are (i) aggregate object tracking based on 3-D motion and structure constraints in constrast with traditional primitive feature tracking based on image motion heuristics, and (ii) use of temporal behavior for object segmentation and 3-D reconstruction.