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Title: | Increasing Robustness of Real-Time Edge-Based Tracking |
Abstract: | In this project, a real-time edge based visual tracking system is developed. It associates visible edge features of three-dimensional CAD model with the target object's representation on the two-dimensional image plane. Therefore a video stream is processed. Current algorithms make it possible to estimate a camera projection from the deviation between image and its projection. Lie groups and corresponding Lie algebra are used because of their efficient parameterization; and simple representation of the motion computations. A least-square approach estimates the projection between two consecutive video frames. Two standard outlier detection algorithms are used to robustify the system. |
Student: | Kenan Bektas |
Director: | Gudrun Klinker |
Supervisor: | Benjamin Becker |
Type: | Master Thesis |
Area: | Computer Vision |
Status: | finished |
Start: | 2007/08/15 |
Finish: | 2008/01/31 |