Review of Stereo Vision Algorithms: From Software to Hardware

By Nalpantidis Lazaros, Georgios Sirakoulis, Antonios Gasteratos. 2008

401 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/f185a5550e90de9d93d43b3fd35b99e5fc6af2e7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Daniel Scharstein
2. Song Zhang
3. Heiko Hirschmüller

In Computer Vision and Pattern Recognition

1. Heiko Hirschmüller
2. Daniel Scharstein
3. Song Zhang
4. York Kitajima
5. Xi Wang
6. Greg Krathwohl
7. Nera Nesic
8. Porter Westling

In Media Technology

1. Heiko Hirschmüller
2. Daniel Scharstein
3. Song Zhang
4. Sam Van der Jeught
5. Joris J. J. Dirckx

Citations in the corpus

• High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth (2014, background): “Stereo vision is one of the most heavily researched topics in computer vision [5, 17, 18, 20, 28], and much of the progress over the last decade has been driven by the availability of standard test images and benchmarks [7, 14, 27, 28, 30, 31].”
• The status, challenges, and future of additive manufacturing in engineering (2015, neutral): “Numerous techniques have been developed including photogrammetry [291], stereovision [292], light field [293], shape from shading [294], time of flight [295], structured light [296], and digital fringe projection [297].”
• High-speed 3D shape measurement with structured light methods: A review (2018, methodology): “The passive techniques use no active illumination for 3D reconstruction with stereo vision [1,2] being one of the most popular methods.”