The effect of feature composition on the localization accuracy of visual SLAM systems

Heshmat, Mohamed and Abdellatif, Mohamed (2012) The effect of feature composition on the localization accuracy of visual SLAM systems. In: International Conference on Computer Vision Theory and Applications, 24 - 26 February 2012, Rome, Italy.

Heshmat VISAPP 2012.pdf
Heshmat VISAPP 2012.pdf - Whole Document

Item Type:Conference or Workshop contribution (Poster)
Item Status:Live Archive


Simultaneous Localization and Mapping, SLAM, for mobile robots using a single camera, has attracted several researchers in the recent years. In this paper, we study the effect of feature point geometrical composition on the associated localization errors. The study will help to design an efficient feature management strategy that can reach high accuracy using fewer features. The basic idea is inspired from camera calibration literature which requires calibration target points to have significant perspective effect to derive accurate camera parameters. When the scene have significant perspective effect, it is expected that this will reduce the errors since it implicitly comply with the utilized perspective projection model. Experiments were done to explore the effect of scene features composition on the localization errors using the state of the art visual Mono SLAM algorithm.

Keywords:Monocular Visual SLAM, Feature Composition, Feature Selection Criteria
Subjects:H Engineering > H671 Robotics
Divisions:College of Science > School of Computer Science
Related URLs:
ID Code:25426
Deposited On:26 Dec 2016 19:58

Repository Staff Only: item control page