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

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Bachelor/Master thesis: Improving User Recognition for an Augmented Reality Magic Mirror

Thesis by:
Advisor: Nassir Navab
Supervision by: Ma Meng
Due date: now

We have previously shown an augmented reality (AR) magic mirror. We create the illusion that a user standing in front of the system can look inside the own body. The video of this system received a lot of attention and has been seen over 200.000 time on Youtube. We now want to build a system for education of human anatomy using augmented reality visualization.

The system has been used previously e.g. during open days and similar events. During the IdeenPark it was used by more than 2000 people. One problem is that it can only be used under supervision. The system cannot automatically detect how big a person is or whether a person is male or female. how to choose the best medical data is based on theseuser features. These parameters must currently be entered manually. Right now we are also working on another project "Real mirror", we want to implement the real mirror function in our system and create more interesting functions, such as what would happen to your body if you get or lose 20 KG. The goal of this thesis is to use simple computer vision and machine learning methods to recognize aspects such as size and gender of the user and to automatically adapt the magic mirror system. So e.g. the angle of the camera has to be changed automatically. Your final task is to create a user recognition layer for the magic mirror system. So other people could develop more smart and interesting applications based on your work.

Title: Improving User Recognition for an Augmented Reality Magic Mirror
Abstract: The goal of this thesis is to improve the recognition of users in an augmented reality system by using simple computer vision and machine learning techniques.
Director: Nassir Navab
Supervisor: Ma Meng
Type: DA/MA/BA
Area: Computer Vision, Medical Augmented Reality
Status: finished
Thesis (optional):  

Edit | Attach | Refresh | Diffs | More | Revision r1.6 - 22 Jan 2016 - 08:08 - MaMeng