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Effcient Multiple Loop Adjustment for Computer Vision Tasks

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Abstract:

Applications performing dead reckoning generally suffer from the inevitable drift of the solutions due to measurement noise and other systematic errors. When dealing with moving sensors such as cameras or laser scanners, loop closing represents one of the most important strategies to compensate for these effects. Imposing loop constraints reduces the uncertainties that arise and permits the construction of consistent maps, mosaics, or scene reconstructions. We propose and demonstrate an approach to correct multiple loops simultaneously by least squares adjustments in 2D and 3D. The results are statistically optimal, since all individual uncertainties and correlations are considered. The use of minimal transformation representations without singularities enables efficient implementation. Furthermore, we address the selection of consistent loop constraints by exploiting the natural order of the sensor datasets given by the acquisition process. The feasibility and the efficiency of the approach are demonstrated using synthetic data reflecting an indoor exploration scenario and by examples for terrestrial and airborne video mosaicking.

German
Die Lösungen von Anwendungen, die eine Koppelnavigation durchführen, weisen in der Regel eine unvermeidbare Drift aufgrund von Messrauschen und restsystematischen Fehlern auf. Konzeptionell stellen Schleifenschlüsse eine wichtige Strategie dar, um diese Effekte zu kompensieren. Die Schleifenbedingungen reduzieren die auftretenden Ungenauigkeiten und gestatten den Aufbau von konsistenten Karten, Mosaiken oder Szenenrekonstruktionen. Wir stellen einen allgemeinen Ansatz vor, um mehrere auftretende Schleifen gleichzeitig in 2D und 3D durch Ausgleichungen zur korrigieren. Die Ergebnisse sind statistisch optimal, da alle individuellen Unsicherheiten und Korrelationen berücksichtigt werden. Die verwendeten minimalen Repräsentationen für Transformationen in 2D bzw. 3D weisen keine Singularitäten auf und ermöglichen eine effiziente Umsetzung. Des Weiteren wird eine Strategie für die Auswahl konsistenter Bedingungsgleichungen vorgestellt, welche sich aufgrund der zeitlichen Reihenfolge der Daten im Erfassungsprozess ergibt. Die Durchführbarkeit und die Effizienz des Ansatzes wird anhand synthetischer Daten demonstriert, die eine Innenraumexploration simulieren, sowie mit Beispielen für die Mosaikierungen von terrestrisch und luftgetragen erfassten Videobildern.

Keywords: IMAGE MOSAICKING; LOOP ADJUSTMENT; SIMULTANEOUS LOCALIZATION AND MAPPING

Document Type: Research Article

DOI: http://dx.doi.org/10.1127/1432-8364/2012/0134

Publication date: October 1, 2012

More about this publication?
  • Photogrammetrie - Fernerkundung - Geoinformation (PFG) is an international scholarly journal covering the progress and application of photogrammetric methods, remote sensing technology and the intricately connected field of geoinformation processing.

    Papers published in PFG highlight new developments and applications of these technologies in practice. The journal hence addresses both researchers and student of these disciplines at academic institutions and universities and the downstream users in both the private sector and public administration.

    PFG places special editorial emphasis on the communication of new methodologies in data acquisition, new approaches to optimized processing and interpretation of all types of data which were acquired by photogrammetric methods, remote sensing, image processing and the computer-aided interpretation of such data in general.

    PFG is the official journal of the German Society of Photogrammetry and Remote Sensing.
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