Thesis Details
Výpočet mapy disparity ze stereo obrazu
The master thesis focuses on disparity map estimation using convolutional neural network. It discusses the problem of using convolutional neural networks for image comparison and disparity computation from stereo image as well as existing approaches of solutions for given problem. It also proposes and implements system that consists of convolutional neural network that measures the similarity between two image patches, and filtering and smoothing methods to improve the result disparity map. Experiments and results show, that the most quality disparity maps are computed using CNN on input patches with the size of 9x9 pixels combined with matching cost agregation and correction algorithm and bilateral filter.
convolutional neural networks, stereo image, disparity, disparity map, caffe
Beran Vítězslav, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Češka Milan, prof. RNDr., CSc. (DITS FIT BUT), člen
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), člen
Vranić Valentino, doc. Ing., Ph.D. (FIIT STU), člen
@mastersthesis{FITMT14887,
author = "Roman T\'{a}bi",
type = "Master's thesis",
title = "V\'{y}po\v{c}et mapy disparity ze stereo obrazu",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2017,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/14887/"
}