Thesis Details
Automatický odhad nadmořské výšky z obrazu
This thesis is concerned with the automatic altitude estimation from a single landscape photograph. I solved this task using convolutional neural networks. There was no suitable training dataset available having information about image altitude, thus I had to create a new one. To estimate human performance in altitude estimation task, an experiment was conducted counting 100 subjects. The goal of this experiment was to measure the accuracy of the human estimate of camera altitude from an image. The measured average estimation error of subjects was 879 m. An automatic system based on convolutional neural networks outperforms humans with an average elevation error 712 m. The proposed system can be used in more complex scenario like the visual camera geo-localization.
Automatic image recognition, altitude estimation, convolutional neural networks
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Sedlák Petr, doc. Ing., Ph.D. (DPHYS FEEC BUT), člen
Szőke Igor, Ing., Ph.D. (DCGM FIT BUT), člen
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY FIT BUT), člen
@mastersthesis{FITMT16497,
author = "Jan Va\v{s}\'{i}\v{c}ek",
type = "Master's thesis",
title = "Automatick\'{y} odhad nadmo\v{r}sk\'{e} v\'{y}\v{s}ky z obrazu",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2015,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/16497/"
}