Approximated Relative Pose Solvers for Efficient Camera Motion Estimation

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• 作者：Jonathan Ventura (16) (17)
  Clemens Arth (17)
  Vincent Lepetit (17)
  
  16. Department of Computer Science ; University of Colorado Colorado Springs ; Colorado Springs ; USA
  17. Institute for Computer Graphics and Vision ; Graz University of Technology ; Graz ; Austria
  
• 关键词：Camera pose ; Relative pose ; Relative orientation ; Five ; pt algorithm ; Essential matrix ; Gr枚bner basis
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：8925
• 期：1
• 页码：180-193
• 全文大小：1,427 KB
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• 作者单位：Computer Vision - ECCV 2014 Workshops
• 丛书名：978-3-319-16177-8
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

We propose simple and efficient methods for estimating the camera motion between two images when this motion is small. While current solutions are still either slow, or unstable in case of small translation, we show how to considerably speed up a recent stable but slow method. The reasons for this speed-up are twofold. First, by approximating the rotation matrix to first order, we obtain a smaller polynomial system to be solved. Second, because of the small rotation assumption, we can use linearization and truncation of higher-order terms to quickly obtain a single solution. Our experiments show that our approach is both stable and fast on challenging test sequences from vehicle-mounted cameras.