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Abstract
The determination of the spatial depth of a scene, which supplies important information for a number of applications, was a very complex matter with previous technologies like stereo cameras or laser scanners and sometimes problematic. With Time-of-Flight cameras there is a technology at hand today, that facilitates the acquisition of these data tremendously. With the Microsoft Kinect 2 Sensor ToF cameras have recently made the jump into the consumer market. Unfortunately these cameras still exhibit different statistical and systematic errors. This thesis shows how the statistical errors can be fixed with the help of methods from 2D image processing and gives for the first time explanations of previously not understood systematic errors by means of an exact analysis of the sensor data. With newly introduced approaches and methods these errors can be reduced notably with little effort and lead to a significant improvement in the accuracy of the measurements.
Document type: | Dissertation |
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Supervisor: | Garbe, PD Dr. Christoph S. |
Date of thesis defense: | 26 November 2014 |
Date Deposited: | 02 Dec 2014 14:13 |
Date: | 2014 |
Faculties / Institutes: | Service facilities > Interdisciplinary Center for Scientific Computing Service facilities > Heidelberg Collaboratory for Image Processing (HCI) |