Multiple view geometry in computer vision
Multiple view geometry in computer vision
Motion and Structure from Image Sequences
Motion and Structure from Image Sequences
Navigation using Affine Structure from Motion
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
An Invitation to 3-D Vision: From Images to Geometric Models
An Invitation to 3-D Vision: From Images to Geometric Models
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
From lines to epipoles through planes in two views
Pattern Recognition
Monocular Vision for Mobile Robot Localization and Autonomous Navigation
International Journal of Computer Vision
Indoor navigation of a non-holonomic mobile robot using a visual memory
Autonomous Robots
Error Analysis in Homography Estimation by First Order Approximation Tools: A General Technique
Journal of Mathematical Imaging and Vision
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Inverse Depth Parametrization for Monocular SLAM
IEEE Transactions on Robotics
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In this paper we propose a new algorithm for relative pose estimation between two images based on a new decomposition for an homography matrix faster than the classical solutions.We introduce in our method approximate information about the planes in the reference images but this additional information allows the decomposition to avoid the multiplicity of solutions. An exhaustive analysis of the error propagation through the method is provided. The new decomposition can be used for visual navigation of robots moving on a planar surface. The approach is based in the well known teaching-by-doing scheme with the route defined by a set of images. The parameters of the planes can be computed automatically from the reference images before the navigation. The contributions are the easy method to extract the parameters of all the planes and the use of this information in navigation tasks using a fast homography decomposition. The experimental results show the performance of the proposal.