Difference between revisions of "User:DanieleFiorenti"
(Created page with "{{Student |category=Student |firstname=Daniele |lastname=Fiorenti |photo=Fiorenti.jpg |email=daniele.fiorenti@mail.polimi.it |advisor=MatteoMatteucci; |resarea=Robotics |statu...") |
(→OpenGL mesh shader and visualizer) |
||
| Line 19: | Line 19: | ||
Depending on the camera point of view we will apply the correct image as a texture to the mesh. | Depending on the camera point of view we will apply the correct image as a texture to the mesh. | ||
This image will be identified thanks to the fact that we have every pose of every camera image with respect to the mesh. | This image will be identified thanks to the fact that we have every pose of every camera image with respect to the mesh. | ||
| + | |||
| + | ===Urban Reconstruction with Texturing=== | ||
| + | |||
| + | Project performed as Master Thesis. | ||
| + | |||
| + | The aim of the project is the creation of an accurate mesh created using data from the KITTI Vision Benchmark Suite. | ||
| + | |||
| + | The point clouds obtained from the velodyne lidar will be registrated togheter and refined with photometric reconstruction algorithm provided by Andrea Romanoni. The mesh obtained with this process will be textured with the photos of the environment. | ||
Latest revision as of 10:40, 5 May 2016
Daniele Fiorenti
| |
 | |
| First Name: | Daniele |
| Last Name: | Fiorenti |
| E-Mail: | daniele.fiorenti@mail.polimi.it |
| Advisor: | |
| Project page(s): | |
| Status: | active |
AIRLab Activities
OpenGL mesh shader and visualizer
The aim of this projects is to develop a software using the OpenGL library for rendering and visualizing a textured mesh. More specifically meshes were obtained from camera images with specific algorithms thanks to the work of Andrea Romanoni.
Depending on the camera point of view we will apply the correct image as a texture to the mesh. This image will be identified thanks to the fact that we have every pose of every camera image with respect to the mesh.
Urban Reconstruction with Texturing
Project performed as Master Thesis.
The aim of the project is the creation of an accurate mesh created using data from the KITTI Vision Benchmark Suite.
The point clouds obtained from the velodyne lidar will be registrated togheter and refined with photometric reconstruction algorithm provided by Andrea Romanoni. The mesh obtained with this process will be textured with the photos of the environment.
