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Author  |
Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan Carlos Moure | ||||
| Title | GPU-accelerated real-time stixel computation | Type | Conference Article | ||
| Year | 2017 | Publication | IEEE Winter Conference on Applications of Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 1054-1062 | ||
| Keywords | Autonomous Driving; GPU; Stixel | ||||
| Abstract | The Stixel World is a medium-level, compact representation of road scenes that abstracts millions of disparity pixels into hundreds or thousands of stixels. The goal of this work is to implement and evaluate a complete multi-stixel estimation pipeline on an embedded, energyefficient, GPU-accelerated device. This work presents a full GPU-accelerated implementation of stixel estimation that produces reliable results at 26 frames per second (real-time) on the Tegra X1 for disparity images of 1024×440 pixels and stixel widths of 5 pixels, and achieves more than 400 frames per second on a high-end Titan X GPU card. | ||||
| Address | Santa Rosa; CA; USA; March 2017 | ||||
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| Area | Expedition | Conference | WACV | ||
| Notes | ADAS; 600.118 | Approved | no | ||
| Call Number | ADAS @ adas @ HEV2017b | Serial | 2812 | ||
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