TY - GEN
T1 - Paris-rue-madame database
T2 - 3rd International Conference on Pattern Recognition Applications and Methods, ICPRAM 2014
AU - Serna, Andrés
AU - Marcotegui, Beatriz
AU - Goulette, François
AU - Deschaud, Jean Emmanuel
PY - 2014/1/1
Y1 - 2014/1/1
N2 - This paper describes a publicly available 3D database from the rueMadame, 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.
AB - This paper describes a publicly available 3D database from the rueMadame, 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.
KW - 3D database
KW - Classification
KW - Mobile laser scanner
KW - Point-wise evaluation
KW - Segmentation
KW - Urban analysis
UR - https://www.scopus.com/pages/publications/84902310695
U2 - 10.5220/0004934808190824
DO - 10.5220/0004934808190824
M3 - Conference contribution
AN - SCOPUS:84902310695
SN - 9789897580185
T3 - ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods
SP - 819
EP - 824
BT - ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods
PB - SciTePress
Y2 - 6 March 2014 through 8 March 2014
ER -