Keywords: Computer Vision
Abstract
In this project, we are interested in the fundamental problem of simultaneously tracking a piecewise-planar scene and accurately estimating the 3D displacement of the camera. The objective is to have an algorithm with a higher convergence frequency and a higher convergence rate than standard optimization methods while having an equivalent computational complexity. Since the tracking is aimed to be used in industrial real-time augmented reality applications, in addition to the robustness and the speed performance, the algorithm should be very precise. For some applications, we are investigating alternatives where an off-line learning step improves the efficiency and the convergence properties of the tracking algorithm.
Pictures
|
|
Figure 1:
|
|
|
|
Figure 2:
|
|
|
|
Figure 3:
|
|
|
|
Figure 4:
|
|
Videos
Publications
Team
Contact Person(s)
Working Group
Alumni
Location
Visit our lab at Garching.
internal project page
Please contact
Selim Benhimane for available student projects within this research project.