GTC 2020: Accelerating Optical Flow and Stereo Disparity Estimation on Nvidia GPUs
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Accelerating Optical Flow and Stereo Disparity Estimation on Nvidia GPUs
Eric Viscito, NVIDIA
Computer vision algorithms in many applications, such as video analytics, robotics, and autonomous vehicles, depend on motion and depth information. Recent GPU SOCs include a new hardware engine—the Optical Flow Accelerator (OFA)—that accelerates the estimation of optical flow and stereo disparity, freeing up the GPU from these tasks. The engine is exposed through high-level APIs and can be integrated into various computer-vision pipelines. We'll introduce the OFA engine, teach its principles and modes of operation, discuss throughput and quality metrics, and illustrate some applications. We're aiming for the general computer-vision engineer, as well as any GPU software engineer desiring a fuller understanding of the capabilities of modern GPUs. In-depth knowledge of optical flow or stereo disparity estimation algorithms is not required, although some pre-existing knowledge in those areas will enable a better appreciation of the principles of operation.