@InProceedings{DanielHernandez2017,
author="Daniel Hernandez
and Antonio Espinosa
and David Vazquez
and Antonio Lopez
and Juan Carlos Moure",
title="GPU-accelerated real-time stixel computation",
booktitle="IEEE Winter Conference on Applications of Computer Vision",
year="2017",
pages="1054--1062",
optkeywords="Autonomous Driving",
optkeywords="GPU",
optkeywords="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{\texttimes}440 pixels and stixel widths of 5 pixels, and achieves more than 400 frames per second on a high-end Titan X GPU card.",
optnote="ADAS; 600.118",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2812), last updated on Tue, 01 Sep 2020 11:48:54 +0200",
doi="10.1109/WACV.2017.122",
opturl="https://ieeexplore.ieee.org/document/7926705",
file=":http://refbase.cvc.uab.es/files/HEV2016.pdf:PDF"
}