University of Oulu

Pose estimation using two line correspondences and gravity vector for image rectification

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Author: Kumar, Kushal1
Organizations: 1University of Oulu, Faculty of Information Technology and Electrical Engineering, Department of Computer Science and Engineering, Computer Science and Engineering
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 19.9 MB)
Persistent link: http://urn.fi/URN:NBN:fi:oulu-201609142782
Language: English
Published: Oulu : K. Kumar, 2016
Publish Date: 2016-09-19
Physical Description: 47 p.
Thesis type: Master's thesis (tech)
Tutor: Heikkilä, Janne
Reviewer: Heikkilä, Janne
Rahtu, Esa
Description:
Pose estimation is a well-studied problem in computer vision. Many solutions which provide high accuracy depend on nonlinear optimization. For real-time applications, linear or closed-form solutions are preferred. Some relatively new methods also fuse inertial sensor data with that from the visual sensor to achieve higher accuracy. We propose a closed-form solution to estimate camera pose using two lines and gravity information. The system is developed so that it could work in unprepared environments which satisfy the Manhattan world assumption. We first test the proposed method on a synthetic data set and compare it to other state-of-the-art point and line based pose estimation methods, comparing their mean rotation and mean translation errors. I.M.U. noise effect on the overall performance of the system is also tested. We then proceed to test our algorithm in real world by rectifying perspective deformed images. The deviation of the calculated pose from the ground-truth pose is calculated for each image to test the real world performance of the proposed algorithm. Also, I.M.U. noise is calculated, which correspond to the 0.5% noise level expected in low cost I.M.U.’s.
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Copyright information: © Kushal Kumar, 2016. This publication is copyrighted. You may download, display and print it for your own personal use. Commercial use is prohibited.