Optical Linear Feature Detection Based on Model Pose

摘要

Low-level edge detection in optical imagery can be problematic in the ATR domainwhere highly complex scenes are the norm. Feature detection algorithms typically take a global approach, resulting in the discovery of many fragmented lines which are not directly related to stored model information. For this domain, we have taken a top-down approach which searches an optical image for the locally optimal features based on the current hypothesized object pose. The resulting linear features can then be matched against a CAD model.