# Embedded real-time stereo estimation via Semi-Global Matching on the GPU

arXiv: https://arxiv.org/abs/1610.04121 · HTML: https://mlsanity.com/paper/1610.04121/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Oct 2016.

## Built on by (most cited first, 13 of 13)

- [Learning High-Speed Flight in the Wild](https://mlsanity.com/paper/2110.05113/) (2021)
- [Dusk Till Dawn: Self-supervised Nighttime Stereo Depth Estimation using Visual Foundation Models](https://mlsanity.com/paper/2405.11158/) (2024)
- [ReS2tAC -- UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices](https://mlsanity.com/paper/2106.07927/) (2021)
- [StereoVAE: A lightweight stereo-matching system using embedded GPUs](https://mlsanity.com/paper/2305.11566/) (2023)
- [An evaluation of Deep Learning based stereo dense matching dataset shift from aerial images and a large scale stereo dataset](https://mlsanity.com/paper/2402.12522/) (2024)
- [Accurate and Real-time Pseudo Lidar Detection: Is Stereo Neural Network Really Necessary?](https://mlsanity.com/paper/2206.13858/) (2022)
- [Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matching](https://mlsanity.com/paper/2210.01436/) (2022)
- [Efficient stereo matching on embedded GPUs with zero-means cross correlation](https://mlsanity.com/paper/2212.00476/) (2022)
- [FaSS-MVS -- Fast Multi-View Stereo with Surface-Aware Semi-Global Matching from UAV-borne Monocular Imagery](https://mlsanity.com/paper/2112.00821/) (2021)
- [Real-Time High-Quality Stereo Matching System on a GPU](https://mlsanity.com/paper/2212.00488/) (2022)
- [A Reinforcement Learning Method for Environments with Stochastic Variables: Post-Decision Proximal Policy Optimization with Dual Critic Networks](https://mlsanity.com/paper/2504.05150/) (2025)
- [ADEPT: Adaptive Diffusion Environment for Policy Transfer Sim-to-Real](https://mlsanity.com/paper/2506.01759/) (2025)
- [Object-Centric Stereo Ranging for Autonomous Driving: From Dense Disparity to Census-Based Template Matching](https://mlsanity.com/paper/2604.07980/) (2026)

## Abstract (arXiv)

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.