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Proceedings Paper

Computational vision approach to stereo video stabilization
Author(s): Xing Fang; Yuhui Gui; Xinyuan Cai
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Paper Abstract

This paper describes a system that estimates the 3D motion of the camera in a cluttered scene containing moving objects from a stereo image sequence. We use KLT[2] trackers to detect and track landmarks in both camera sequences. Range information gives an approximation of the depth for the landmarks and helps us to build a 3D system equation for the scene. By taking a novel method to detect outliers in landmark set from depth discontinuities, the filtered landmarks are then run through an iterated weighted linear square method with a retiring scheme. The estimated ego motion helps warp images of the scene, which enables us to find foreground objects from stabilized images. We describe the overall system as well as the details of the stabilization along with images that show the results of the stabilization results.

Paper Details

Date Published: 25 February 2005
PDF: 8 pages
Proc. SPIE 5671, Real-Time Imaging IX, (25 February 2005); doi: 10.1117/12.586968
Show Author Affiliations
Xing Fang, Wuhan Univ. of Technology (China)
Yuhui Gui, Wuhan Univ. of Technology (China)
Xinyuan Cai, Wuhan Univ. of Technology (China)

Published in SPIE Proceedings Vol. 5671:
Real-Time Imaging IX
Nasser Kehtarnavaz; Phillip A. Laplante, Editor(s)

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