Object recognition using low light level 3D point clouds

Abstract

Target recognition is a key aspect for many applications. Rapidly maturing small sensor platforms continually require better, more agile sensor performance coupled with smaller, lighter, and faster sensor implementations. Additionally, longer range applications necessitate more efficient use of photons received from active illumination. We describe a potential approach to overcoming both issues based on photon counting laser radar, which performs pattern recognition using images with very few detected photo-events. Previous work using intensity images show near ideal pattern recognition with as low as 50 photo-detections. We investigate through simulation an extension of prior work to 3D point cloud imagery.