Mosaicking Cluttered Ground Planes Based on Stereo Vision

Authors:
José Gaspar;Miguel Realpe;Boris Vintimilla;José Santos-Victor
Affiliations:
Computer Vision Laboratory Inst. for Systems and Robotics Instituto Superior Técnico Lisboa, Portugal;Vision and Robotics Center Dept. of Electrical and Computer Science Eng., Escuela Superior Politécnica del Litoral Guayaquil, Ecuador,;Vision and Robotics Center Dept. of Electrical and Computer Science Eng., Escuela Superior Politécnica del Litoral Guayaquil, Ecuador,;Computer Vision Laboratory Inst. for Systems and Robotics Instituto Superior Técnico Lisboa, Portugal
Venue:
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Year:
2007

Citing 6
Cited 0

A Method for Registration of 3-D Shapes

IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Three-dimensional computer vision: a geometric viewpoint

Three-dimensional computer vision: a geometric viewpoint
Multiple view geometry in computer vision

Multiple view geometry in computer vision
The Trimmed Iterative Closest Point Algorithm

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Real-Time Simultaneous Localisation and Mapping with a Single Camera

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Vision-based global localization and mapping for mobile robots

IEEE Transactions on Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recent stereo cameras provide reliable 3D reconstructions. These are useful for selecting ground-plane points, register them and building mosaics of cluttered ground planes. In this paper we propose a 2D Iterated Closest Point (ICP) registration method, based on the distance transform, combined with a fine-tuning-registration step using directly the image data. Experiments with real data show that ICP is robust to 3D reconstruction differences due to motion and the fine tuning step minimizes the effect of the uncertainty in the 3D reconstructions.