Project Details

Topografická analýza obrazu s využitím metod hlubokého učení

Project Period: 1. 7. 2019 - 30. 6. 2022

Project Type: grant

Code: LTAIZ19004

Agency: Ministry of Education, Youth and Sports Czech Republic

Program: INTER-EXCELLENCE - Podprogram INTER-ACTION

English title
Deep-Learning Approach to Topographical Image Analysis
Type
grant
Keywords

image geo-localization, topographic information, image registration, deep-learning, computer vision

Abstract

The project focuses on the current problems of computer vision, especially on visual localization in the natural environment. The visual location of the camera in the outdoor environment is not a fixed issue today, although it offers a wide range of attractive applications from automatic image comprehension, to expanded reality applications to navigation of self-governing vehicles and airplanes. The project aims to research new methods for locating cameras based on the multimodal data registration, especially photographic information, synthetic rendered images, depth information and field models using current machine learning methods, especially deep neural networks (DNN). In addition to the use of terrain data in the form of graphical models, an alternative of predictive depth information from an input photograph will be explored. The CPhoto @ FIT Group has been dealing with the long-standing problem and has deep experience in research and application. The Israeli partner also offers unique data sets indispensable for DNN training.

Team members
Čadík Martin, doc. Ing., Ph.D. (UPGM FIT VUT) , research leader
Brejcha Jan, Ing., Ph.D. (UPGM FIT VUT)
Lysek Tomáš, Ing. (UPGM FIT VUT)
Polášek Tomáš, Ing. (UPGM FIT VUT)
Tomešek Jan, Ing. (UPGM FIT VUT)
Publications

2024

2023

2022

2021

2020

Products

2022

2020

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