Automatic absolute and relative camera egomotion estimation based on visual features

Aufderheide, Dominik, Krybus, Werner and Edwards, Gerard (2012) Automatic absolute and relative camera egomotion estimation based on visual features. In: Research and Innovation Conference 2012, 26 - 27 June 2012, Bolton. (Unpublished)

[img] PDF
D Aufderheide et al R I Conf (2012) Proceedings Paper.pdf

Download (1MB)

Abstract

The automatic estimation of a cameras position based on visual measurements is a general problem in the field of computer vision. Based on the estimated cameras trajectory it is possible to solve common tasks, such as Visual Odometry (VO) in the field of mobile robotics or the automatic reconstruction of an observed scene, based on classical Structure-from-Motion (SfM) techniques. The general procedure of camera egomotion estimation is always based on visual feature tracking and subsequent Perspective-n-Point (PnP) camera pose determination. This article evaluates recent algorithms for camera egomotion estimation based on point feature correspondences for their applicability in VO applications. These algorithms use methods based on 2D/2D and 3D/2D correspondences and are assessed in experimental evaluations employing synthetic data sets. It was found that the accuracy of the evaluated techniques is predominantly influenced by the number of correspondences and underlying motion patterns. Additional routines such as outlier handling and key frame detection were found to be mandatory for real-world application.

Item Type: Conference or Workshop Item (Paper)
Additional Information: This paper was originally presented at the University of Bolton Research and Innovation Conference 2012, Bolton, 26 - 27 June 2012.
Uncontrolled Keywords: Camera egomotion estimation,Pose Estimation, Perspective-n-Point (PnP) problem, Simultaneous localisation and mapping (SLAM), Structure from motion (SfM) PnP-problem
Divisions: University of Bolton Conferences > Research and Innovation Conference > Research and Innovation Conference 2012
Depositing User: Scott Wilson
Date Deposited: 26 Nov 2013 12:53
Last Modified: 16 Dec 2013 11:03
URI: http://ubir.bolton.ac.uk/id/eprint/565

Actions (login required)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics

>