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Event Entry
New for: D2, D3
What and Who
Linear Camera Pose Estimation from 3D to 2D Feature Correspondences
Caigui Jiang
Xi'an Jiaotong University
PhD Application Talk
Master student
AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI
Public Audience
English
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Date, Time and Location
Monday, 21 February 2011
14:00
120 Minutes
E1 4
R024
Saarbrücken
Abstract
Camera pose estimation from 3D to 2D feature correspondence has received a lot of attention in the past two decades. It has been widely used in the field of computer vision, robot navigation, photogrammetry, augmented reality (AR) and so on. The linear pose estimation algorithm is significant not only for reasons of efficiency but also because an accurate linear solution provides a well initial for other iterative algorithms, resulting in their faster and efficient convergence. My research strives to conceive some algorithms which can efficiently and accurately determine the camera pose applying different 3D to 2D corresponding features involving point, line and combined point and line features. For the point corresponding feature algorithm, the angle constraints were applied to create the constraint function. In the line corresponding feature algorithm, the rotation matrix was represented by unit quaternion parameters. The constraint functions of these parameters were conducted. To extend the line algorithm, the algorithm based on the combination features of line and point was proposed. These algorithm was tested by simulation experiments and real image experiments .
Contact
IMPRS-CS Office
0681 93 25 225
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Heike Przybyl, 02/17/2011 15:41 -- Created document.