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2017 GTC San Jose

S7473 - Towards a Fully Automated, High-Performance Pipeline for Stereo Reconstruction from Earth Observing Satellites

Session Speakers
Session Description

Learn how CPU-GPU parallelization is used for high-throughput 3D surface point cloud generation from Earth-observing satellites. Stereo photogrammetry, used in computer vision applications, analyzes the parallax between image pairs to estimate depth. However, extending this workflow to satellite imagery presents computational challenges; notably, near-continuous streams of gigapixel-sized images. We leverage multicore and multiple Tesla K80 GPUs to assemble a fully automated pipeline capable of rapidly processing large image streams. Initial timings demonstrated an 89x (~10x over OpenMP, multicore scaling) performance improvement over its publicly available version. We'll share lessons learned in extending stereo reconstruction algorithms into satellite imaging, at scale.


Additional Session Information
Intermediate
Talk
Computer Vision and Machine Vision Deep Learning and AI HPC and Supercomputing
25 minutes
Session Schedule