Active high dynamic range mapping for dense visual SLAM

Autor: Andrew I. Comport, Christian Barat
Přispěvatelé: Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe SYSTEMES, Signal, Images et Systèmes (Laboratoire I3S - SIS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2017
Předmět:
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
Simultaneous localization and mapping
[SPI.AUTO]Engineering Sciences [physics]/Automatic
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Shutter
Computer graphics (images)
0202 electrical engineering
electronic engineering
information engineering
[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]
Computer vision
High dynamic range
ComputingMethodologies_COMPUTERGRAPHICS
business.industry
Dynamic range
Perspective (graphical)
Photography
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Radiance
RGB color model
020201 artificial intelligence & image processing
Artificial intelligence
business
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Texture mapping
Reflection mapping
Zdroj: IROS
IEEE/RSJ International Conference on Intelligent Robots and Systems
IEEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2017, Vancouver, Canada
DOI: 10.1109/iros.2017.8206560
Popis: International audience; — Acquiring High Dynamic Range (HDR) photos from several images, with an active shutter providing different exposures (sensor integration periods), has been widely commercialised in photography for static camera positions. In the case of a mobile video sensor (as is the case in robotics), this problem is more difficult due to real-time motion of the sensor which transforms the perspective between the acquired images. HDR approaches for a set of images from different perspectives have therefore been significantly overlooked since this would require sophisticated dense mapping approaches to eliminate the motion component. Recent dense visual SLAM (Simultaneous Localization And Mapping) approaches provide this framework, however, few works have attempted to perform HDR visual SLAM. Current approaches are thus highly depen-dant on illumination conditions and camera shutter settings. In this paper a new approach is proposed that enables 3D HDR environment maps to be acquired actively from a dynamic set of images in real-time. The 6 DOF pose, the dense scene structure and the HDR texture map will be estimated simultaneously with the objective of maximising the dynamic range. This will allow to obtain a radiance map of the scene by fusing a real-time stream of low dynamic range images (LDR) into a graph of HDR key-frame images. In particular, a method is proposed to actively control the shutter based on information theory to optimise the information content of the 3D HDR environment map for RGB-D sensors. As will be shown in the results, a 3D HDR environment map allows robot localisation and mapping (visual SLAM) to take actively advantage of varying luminosity in different parts of the scene.
Databáze: OpenAIRE
Externí odkaz: