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VOPT: Robust Visual Odometry by Simultaneous Feature Matching and Camera Calibration

Topics: Active and Robot Vision; Entertainment Imaging Applications; Human and Computer Interaction; Image Formation, Acquisition Devices and Sensors; Image Registration; Object Detection and Localization; Optical Flow and Motion Analyses; Stereo Vision and Structure from Motion

Authors: Rafael F. V. Saracchini 1 ; Carlos Catalina 1 ; Rodrigo Minetto 2 and Jorge Stolfi 3

Affiliations: 1 Technological Institute of Castilla y León, Spain ; 2 Federal University of Technology of Paraná, Brazil ; 3 State University of Campinas, Brazil

ISBN: 978-989-758-175-5

Keyword(s): 3D Tracking, Augmented Reality, Camera Calibration, Real-time and GPU Processing.

Related Ontology Subjects/Areas/Topics: Active and Robot Vision ; Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Enterprise Information Systems ; Entertainment Imaging Applications ; Human and Computer Interaction ; Human-Computer Interaction ; Image and Video Analysis ; Image Formation and Preprocessing ; Image Formation, Acquisition Devices and Sensors ; Image Registration ; Motion, Tracking and Stereo Vision ; Optical Flow and Motion Analyses ; Stereo Vision and Structure from Motion

Abstract: In this paper we describe VOPT, a robust algorithm for visual odometry. It tracks features of the environment with known position in space, which can be acquired through monocular or RGBD SLAM mapping algorithms. The main idea of VOPT is to jointly optimize the matching of feature projections on successive frames, the camera’s extrinsic matrix, the photometric correction parameters, and the weight of each feature at the same time, by a multi-scale iterative procedure. VOPT uses GPU acceleration to achieve real-time performance, and includes robust procedures for automatic initialization and recovery, without user intervention. Our tests show that VOPT outperforms the PTAMM algorithm in challenging videos available publicly.

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Paper citation in several formats:
Saracchini, R.; Saracchini, R.; Catalina, C.; Catalina, C.; Minetto, R.; Minetto, R. and Stolfi, J. (2016). VOPT: Robust Visual Odometry by Simultaneous Feature Matching and Camera Calibration.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 59-66. DOI: 10.5220/0005781700590066

@conference{visapp16,
author={Rafael F. V. Saracchini. and Rafael F. V. Saracchini. and Carlos Catalina. and Carlos Catalina. and Rodrigo Minetto. and Rodrigo Minetto. and Jorge Stolfi.},
title={VOPT: Robust Visual Odometry by Simultaneous Feature Matching and Camera Calibration},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={59-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005781700590066},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - VOPT: Robust Visual Odometry by Simultaneous Feature Matching and Camera Calibration
SN - 978-989-758-175-5
AU - Saracchini, R.
AU - Saracchini, R.
AU - Catalina, C.
AU - Catalina, C.
AU - Minetto, R.
AU - Minetto, R.
AU - Stolfi, J.
PY - 2016
SP - 59
EP - 66
DO - 10.5220/0005781700590066

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