Paris-rue-Madame Database - A 3D Mobile Laser Scanner Dataset for Benchmarking Urban Detection, Segmentation and Classification Methods
Author(s) -
Andrés Serna,
Beatriz Marcotegui,
François Goulette,
JeanEmmanuel Deschaud
Publication year - 2014
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5220/0004934808190824
Subject(s) - benchmarking , computer science , segmentation , annotation , class (philosophy) , artificial intelligence , object (grammar) , computer vision , point cloud , object detection , point (geometry) , image segmentation , database , pattern recognition (psychology) , mathematics , geometry , marketing , business
This paper describes a publicly available 3D database from the rue Madame, a street in the 6th Parisian district. Data have been acquired by the Mobile Laser Scanning (MLS) system L3D2 and correspond to a 160 m long street section. Annotation has been carried out in a manually assisted way. An initial annotation is obtained using an automatic segmentation algorithm. Then, a manual refinement is done and a label is assigned to each segmented object. Finally, a class is also manually assigned to each object. Available classes include facades, ground, cars, motorcycles, pedestrians, traffic signs, among others. The result is a list of (X, Y, Z, reflectance, label, class) points. Our aim is to offer, to the scientific community, a 3D manually labeled dataset for detection, segmentation and classification benchmarking. With respect to other databases available in the state of the art, this dataset has been exhaustively annotated in order to include all available objects and to allow point-wise comparison.
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