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Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez | ||||
Title | Stereo Matching using SGM on the GPU | Type | Report | ||
Year | 2016 | Publication | Programming and Tuning Massively Parallel Systems | Abbreviated Journal | PUMPS |
Volume | Issue | Pages | |||
Keywords | CUDA; Stereo; Autonomous Vehicle | ||||
Abstract | Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. | ||||
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Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | PUMPS | ||
Notes | ADAS; 600.085; 600.087; 600.076 | Approved | no | ||
Call Number | ADAS @ adas @ HCE2016b | Serial | 2776 | ||
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