Presentation + Paper
30 April 2018 Object recognition using low light level 3D point clouds
Author Affiliations +
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.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kaitlyn M. Jones and Edward A. Watson "Object recognition using low light level 3D point clouds", Proc. SPIE 10648, Automatic Target Recognition XXVIII, 106480A (30 April 2018); https://doi.org/10.1117/12.2304659
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KEYWORDS
Photons

Clouds

Photon counting

Pattern recognition

3D image processing

Image resolution

LIDAR

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