This praktikum introduces common tools and principles in computer vision and machine learning for object recognition and pose estimation, for applications in the field of Augmented Reality and Robotics. Starting from the basics, students are gradually taught to develop a framework that can process images and 3D data with the goal of perceiving shapes and recognizing objects in real environments, under pose variations, clutter and occlusion.
Lecturers: PD Dr. Federico Tombari| TeachingForm | |
|---|---|
| Title: | Perception and Learning in Robotics and Augmented Reality |
| Professor: | PD Dr. Federico Tombari |
| Tutors: | Helisa Dhamo, Fabian Manhardt, Alexander Winkler |
| Type: | Praktikum |
| Information: | 6 SWS, 10 ECTS Credits (IN2106) |
| Term: | 2020SoSe |
| Abstract: | This praktikum introduces common tools and principles in computer vision and machine learning for object recognition and pose estimation, for applications in the field of Augmented Reality and Robotics. Starting from the basics, students are gradually taught to develop a framework that can process images and 3D data with the goal of perceiving shapes and recognizing objects in real environments, under pose variations, clutter and occlusion. |
