TeachingSS20PLARR

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Praktikum/Lab Course - Perception and Learning in Robotics and Augmented Reality

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
Tutors: Helisa Dhamo, Fabian Manhardt, Alexander Winkler
Type: Master Practical Course Module IN2106
Course Title: Perception and Learning in Robotics and Augmented Reality - Link to TUMOnline

Programs lab course: Biomedical Computing (Master), Informatics (Master), Informatics (Diploma)
Programs elective course: Electrical Engineering, Mechanical Engineering, School of Management
SWS: 6
ECTS: 10 Credits

Meetings:
Preliminary Meeting: on Wed 05.02.2020, 16:00 , Location: 01.10.011 . See slides for more info.
The praktikum will take place on Fridays, 3pm-5pm. The exact schedule will be announced soon.

The course will be conducted in English.



Important News

  • If interested in registering for the Praktikum, you can send us your motivation letter/email at plarr-2020[at]googlegroups.com, until 12.02.2020. We look forward to see your reasons for attending the praktikum, related courses you have taken as well as experience in computer vision. However, please note that the official application has to be done via the TUM Matching System.
  • The slides of the preliminary meeting can be found here.

Schedule

Date Location Topic Assignments Conducted by Material Due
TBA            


Projects

Topic Project Description Mentor Team Presentation Schedule
TBA        




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.


Edit | Attach | Refresh | Diffs | More | Revision r1.7 - 06 Feb 2020 - 14:23 - HelisaDhamo

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