CVOct 13, 2016

GPU-accelerated real-time stixel computation

arXiv:1610.04124v117 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the need for efficient, real-time processing in autonomous driving or robotics, but it is incremental as it focuses on optimizing an existing method for specific hardware.

The paper tackled the problem of real-time stixel computation for road scene representation by implementing a GPU-accelerated pipeline, achieving 26 frames per second on an embedded Tegra X1 device and over 400 frames per second on a high-end Titan X GPU.

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, energy-efficient, 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 1024x440 pixels and stixel widths of 5 pixels, and achieves more than 400 frames per second on a high-end Titan X GPU card.

Code Implementations1 repo
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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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