Stereo Matching for Martian Surface Depth Estimation on a Single-Board Computer

Stereo Matching for Martian Surface Depth Estimation on a Single-Board Computer

Lau, Chy (TU Delft Aerospace Engineering)

Speretta, S. (mentor)
Guo, J. (graduation committee)
Root, B.C. (graduation committee)

Delft University of Technology

Aerospace Engineering

2021-08-31

Stereo matching, the process of inferring depth maps from stereo images, is one of the most heavily investigated topics in computer vision. It is part of the first module of navigation systems of planetary rovers, e.g., NASA’s Mars Exploration Rover (MER) missions, NASA’s Mars Science Laboratory (MSL) mission, and ESA’s ExoMars mission. Many stereo matching algorithms, traditional and deep learning based, are available and their performance is typically evaluated on indoor objects or outdoor city scenes. In this thesis, our goal is to improve insight into the performance of stereo matching algorithms for the Martian surface on a single-board computer. First, we search for and compare stereo matching algorithms ranked on stereo vision datasets to obtain a manageable set of algorithms and verify their implementations. Second, we derive performance metrics from the requirements and validate our set of verified algorithms on the Katwijk Beach Planetary Rover dataset. Through experimental evaluation, we gain insight into the performance of four stereo matching algorithms.

stereo vision
deep learning
disparity
stereo matching
Mars
Martian surface
single-board computer

http://resolver.tudelft.nl/uuid:633b0bb6-4205-453c-ba76-304eae2778fa

Student theses

master thesis

© 2021 Chy Lau