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

10/13/2016
by   Daniel Hernandez-Juarez, et al.
0

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.

READ FULL TEXT
research
10/13/2016

GPU-accelerated real-time stixel computation

The Stixel World is a medium-level, compact representation of road scene...
research
01/27/2020

A Robust Real-Time Computing-based Environment Sensing System for Intelligent Vehicle

For intelligent vehicles, sensing the 3D environment is the first but cr...
research
07/07/2020

Single Storage Semi-Global Matching for Real Time Depth Processing

Depth-map is the key computation in computer vision and robotics. One of...
research
10/09/2014

Genetic Stereo Matching Algorithm with Fuzzy Fitness

This paper presents a genetic stereo matching algorithm with fuzzy evalu...
research
06/12/2017

Exploring Computation-Communication Tradeoffs in Camera Systems

Cameras are the defacto sensor. The growing demand for real-time and low...
research
05/07/2019

Fully Parallel Architecture for Semi-global Stereo Matching with Refined Rank Method

Fully parallel architecture at disparity-level for efficient semi-global...
research
03/08/2019

Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures

Modern neural network-based algorithms are able to produce highly accura...

Please sign up or login with your details

Forgot password? Click here to reset