Camera preparation and performance for 3D luminance mapping of road environments

Road lighting measurements are executed with stationary imaging luminance photometry. In these measurements, a digital camera is utilized to create 2D luminance data maps of the scenery. We consider the third dimension to be a meaningful advancement for luminance data presentation and analysis. Hence, we present the preparation for a digital camera in order to use it as an imaging luminance photometer combined with a laser scanning system. The target area of use for our measuring system is the night-time road environment. We assessed the limiting factors when integrating luminance photometry into laser scanning systems. We achieved the initial luminance data and 3D point cloud integration for terrestrial laser scanning (TLS) and mobile laser scanning (MLS) systems. In stationary luminance measurements, the target luminance range was achieved. For mobile measurements, the target luminance range was compromised. The mobile measurement luminance range was limited because a long exposure time could not be used. A short exposure time was compensated for by increasing the sensor sensitivity, which reduced the signal-to-noise ratio. In mobile measurements, the luminance range can be extended towards the low end only by reducing the movement velocity or by accepting more motion blur in the measurements.

[1]  Ismael Colomina,et al.  First Results of a Tandem Terrestrial-Unmanned Aerial mapKITE System with Kinematic Ground Control Points for Corridor Mapping , 2017, Remote. Sens..

[2]  Yi Lin,et al.  Development of a UAV-MMS-Collaborative Aerial-to-Ground Remote Sensing System – A Preparatory Field Validation , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  Kevin W. Houser,et al.  Toward the Accuracy of Lighting Simulations in Physically Based Computer Graphics Software , 1999 .

[4]  Jean-Yves Bouguet,et al.  Camera calibration toolbox for matlab , 2001 .

[5]  Juha Hyyppä,et al.  Mobile mapping : road environment mapping using mobile laser scanning : final report , 2013 .

[6]  Martin Rutzinger,et al.  Extraction of Vertical Walls from Mobile Laser Scanning Data for Solar Potential Assessment , 2011, Remote. Sens..

[7]  Pedro Arias,et al.  Automatic detection of road tunnel luminaires using a mobile LiDAR system , 2014 .

[8]  Juha Hyyppä,et al.  An Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept , 2016, Remote. Sens..

[9]  Stephen Lin,et al.  Single-Image Vignetting Correction , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Mehlika Inanici,et al.  Evaluation of high dynamic range photography as a luminance data acquisition system , 2006 .

[11]  A. Ambekar,et al.  Characterization of display pyrotechnic propellants: Colored light , 2017 .

[12]  Isabelle Tarride.  Electropedia: The World's Online Electrotechnical Vocabulary , 2018 .

[13]  Juha Hyyppä,et al.  Luminance-Corrected 3D Point Clouds for Road and Street Environments , 2015, Remote. Sens..

[14]  Alberto Guarnieri,et al.  Automatic registration of large range datasets with spin-images , 2011 .

[15]  Marjukka Puolakka,et al.  Recommended system for mesopic photometry based on visual performance , 2010 .

[16]  Marc Pollefeys,et al.  Robust Radiometric Calibration and Vignetting Correction , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Elisabetta Rosina,et al.  Generation of a GIS-based environment for infrared thermography analysis of buildings , 2012, Other Conferences.

[18]  Yuwei Chen,et al.  Multiplatform Mobile Laser Scanning: Usability and Performance , 2012, Sensors.

[19]  Khalid M. Mosalam,et al.  Ubiquitous luminance sensing using the Raspberry Pi and Camera Module system , 2017 .

[20]  Hongyi Cai,et al.  Improving the quality of high dynamic range images , 2011 .

[21]  Hongyi Cai,et al.  Measuring Light and Geometry Data of Roadway Environments with a Camera , 2014 .

[22]  D. C. Brown,et al.  Lens distortion for close-range photogrammetry , 1986 .

[23]  Harri Kaartinen,et al.  Multiplatform mobile laser scanning , 2019, Laser Scanning.

[24]  Nadarajah Narendran,et al.  A flicker perception metric , 2016 .

[25]  S. J. Oude Elberink,et al.  RAIL TRACK DETECTION AND MODELLING IN MOBILE LASER SCANNER DATA , 2013 .

[26]  Juha Hyyppä,et al.  Detection of Vertical Pole-Like Objects in a Road Environment Using Vehicle-Based Laser Scanning Data , 2010, Remote. Sens..

[27]  Yi Lin,et al.  Mini-UAV-Borne LIDAR for Fine-Scale Mapping , 2011, IEEE Geoscience and Remote Sensing Letters.

[28]  Carlo Tomasi.  Camera Calibration , 2002 .

[29]  Arko Lucieer,et al.  Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing , 2012, Remote. Sens..

[30]  Domenica Costantino,et al.  QUALITATIVE AND QUANTITATIVE EVALUATION OF THE LUMINANCE OF LASER SCANNER RADIATION FOR THE CLASSIFICATION OF MATERIALS , 2013 .

[31]  Keyi Wang,et al.  Photometric Calibration and Image Stitching for a Large Field of View Multi-Camera System , 2016, Sensors.

[32]  Domenica Costantino,et al.  Production of DTM quality by TLS data , 2013 .

[33]  Qingquan Li,et al.  Automated extraction of street-scene objects from mobile lidar point clouds , 2012 .

[34]  Duane C. Brown,et al.  Close-Range Camera Calibration , 1971 .

[35]  Marjukka Eloholma,et al.  Road lighting - luminance and visibility measurements , 2001 .

[36]  Ryosuke Shibasaki,et al.  AUTO-EXTRACTION OF URBAN FEATURES FROM VEHICLE-BORNE LASER DATA , 2002 .

[37]  Juha Hyyppä,et al.  Tree Classification with Fused Mobile Laser Scanning and Hyperspectral Data , 2011, Sensors.

[38]  Hannu Hyyppä,et al.  Tutorial: Road Lighting for Efficient and Safe Traffic Environments , 2017 .

[39]  Xin Zhang,et al.  Road lighting and headlights: Luminance measurements and automobile lighting simulations , 2008 .

[40]  Chao Liu,et al.  THE APPLICATION OF GIS 3D MODELING AND ANALYSIS TECHNOLOGY IN REAL ESTATE MASS APPRAISAL —— TAKING LANDSCAPE AND SUNLIGHT FACTORS AS THE EXAMPLE , 2014 .

[41]  Martin Moeck,et al.  Validation of High Dynamic Range Imaging to Luminance Measurement , 2005 .

[42]  Dan B. Goldman,et al.  Vignette and exposure calibration and compensation , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[43]  Jianping Wu,et al.  A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data , 2013, Remote. Sens..

[44]  Dietmar Wüller,et al.  The usage of digital cameras as luminance meters , 2007, Electronic Imaging.

[45]  Peter D. Hiscocks,et al.  Measuring Luminance with a Digital Camera , 2011 .

[46]  Stephen Lin,et al.  Single-image vignetting correction using radial gradient symmetry , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[47]  Juha Hyyppä,et al.  Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping , 2008, Sensors.

[48]  Arun Kumar Pratihast,et al.  Detection and modelling of 3D trees from mobile laser scanning data , 2010 .

[49]  Yi Lin,et al.  A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements , 2010 .