Completing Facades: Difference between revisions
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== Introduction == | == Introduction == | ||
Venice is a unique city with both cultural and historical significance. Digital copies of cities and historical cites allows us to preserve and understand them better. Photogrammetry is a technology that can be used to do this which uses images and scans to create models of real world objects and sites. However, due to the nature of the technology there are often holes, missing regions and noise in the data. This project aims to fill in holes in data of facades in Venice. For this 2D images from photogrammetry of Venice is used. The dataset includes completed and incomplete facades. To acheive this aim a method for detecting holes in facades is developed. Investigating if other data types improve reconstruction. | |||
== Project Timeline & Milestones == | == Project Timeline & Milestones == | ||
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== Methodology == | == Methodology == | ||
In order to fill the holes in the images they first need to be detected. | |||
Creating training/validation data | |||
Model for detecting holes | |||
Attaching historical data to facades data | |||
In order to get more data historical data Cadastre 1808. | |||
== Results == | == Results == | ||
Latest revision as of 11:24, 17 November 2024
Introduction
Venice is a unique city with both cultural and historical significance. Digital copies of cities and historical cites allows us to preserve and understand them better. Photogrammetry is a technology that can be used to do this which uses images and scans to create models of real world objects and sites. However, due to the nature of the technology there are often holes, missing regions and noise in the data. This project aims to fill in holes in data of facades in Venice. For this 2D images from photogrammetry of Venice is used. The dataset includes completed and incomplete facades. To acheive this aim a method for detecting holes in facades is developed. Investigating if other data types improve reconstruction.
Project Timeline & Milestones
| Week | Milestones |
|---|---|
| Week 1 | |
| Week 2 | |
| Week 3 | |
| Week 4 | |
| Week 5 | |
| Week 6 | |
| Week 7 |
Methodology
In order to fill the holes in the images they first need to be detected.
Creating training/validation data
Model for detecting holes
Attaching historical data to facades data In order to get more data historical data Cadastre 1808.