Paris-rue-madame database: A 3D mobile laser scanner dataset for benchmarking urban detection, segmentation and classification methods

ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods

Volumn , Issue , 2014, Pages 819-824

  Serna, Andrés ^a   Marcotegui, Beatriz ^a   Goulette, François ^a   Deschaud, Jean Emmanuel ^a  

^a PSL RESEARCH UNIVERSITY   (France)

Author keywords

3D database; Classification; Mobile laser scanner; Point wise evaluation; Segmentation; Urban analysis

Indexed keywords

BENCHMARKING; DATABASE SYSTEMS; IMAGE SEGMENTATION; LASER APPLICATIONS; PATTERN RECOGNITION; SCANNING; TRAFFIC SIGNS;

3D DATABASE; AUTOMATIC SEGMENTATIONS; CLASSIFICATION METHODS; LASER SCANNER; POINT WISE; SCIENTIFIC COMMUNITY; SEGMENTED OBJECTS; URBAN ANALYSIS;

CLASSIFICATION (OF INFORMATION);

EID: 84902310695     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5220/0004934808190824     Document Type: Conference Paper

References (13)

1. CoE LaSR (2013). Centre of Excellence in Laser Scanning Research. Finnish Geodetic Institut. http://www.fgi.fi/coelasr/(Last accessed: December 16, 2013).
2. Golovinskiy, A., Kim, V., and Funkhouser, T. (2009). Shape-based recognition of 3D point clouds in urban environments. In IEEE International Conference on Computer Vision, pages 2154-2161. Kyoto, Japan.
3. Goulette, F., Nashashibi, F., Ammoun, S., and Laurgeau, C. (2006). An integrated on-board laser range sensing system for On-the-Way City and Road Modelling. The ISPRS International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVI-1:1-6.
4. Hernandez, J. and Marcotegui, B. (2009). Filtering of artifacts and pavement segmentation from mobile Li- DAR data. The ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVIII-3/W8:329-333.
5. IGN (2013). IGN - Geospatial and Terrestrial Imagery. IGN French National Mapping Agency. http://isprs.ign.fr/homeen.htm (Last accessed: October 28, 2013).
6. ISPRS (2013). The ISPRS data set collection. ISPRS International Society for Photogrammetry and Remote Sensing. http://www.isprs.org/data/(Last accessed: October 28, 2013).
7. Munoz, D., Bagnell, J. A., Vandapel, N., and Herbert, M. (2009). Contextual Classification with Functional Max-Margin Markov Networks. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR).
8. Nuchter, A. and Lingemann, K. (2011). Robotic 3D Scan Repository. Jacobs University Bremen gGmbH and University of Osnabruck. http://kos.informatik. uniosnabrueck.de/3Dscans/(Last accessed: December 16, 2013).
9. Serna, A. and Marcotegui, B. (2013a). Attribute controlled reconstruction and adaptive mathematical morphology. In 2013 International Symposium on Mathematical Morphology (ISMM), pages 207-218, Uppsala, Sweden.
10. Serna, A. and Marcotegui, B. (2013b). Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning. {ISPRS} Journal of Photogrammetry and Remote Sensing, 0(0):1. (Accepted).
11. Serna, A. and Marcotegui, B. (2013c). Urban accessibility diagnosis from mobile laser scanning data. ISPRS Journal of Photogrammetry Remote Sensing, 84:23- 32.
12. Velodyne (2012). The HDL-32E Velodyne LiDAR sensor. Velodyne Lidar 2012. http://velodynelidar.com/lidar/hdlproducts/hdl32e.aspx (Last accessed: December 16, 2013).
13. Zhou, L. and Vosselman, G. (2012). Mapping curbstones in airborne and mobile laser scanning data. International Journal of Applied Earth Observation and Geoinformation, 18(1):293-304.