TY - JOUR
T1 - Processing of Extremely High Resolution LiDAR and RGB Data
T2 - Outcome of the 2015 IEEE GRSS Data Fusion Contest-Part B: 3-D Contest
AU - Vo, A. V.
AU - Truong-Hong, L.
AU - Laefer, D. F.
AU - Tiede, D.
AU - Doleire-Oltmanns, S.
AU - Baraldi, A.
AU - Shimoni, M.
AU - Moser, G.
AU - Tuia, D.
N1 - Publisher Copyright:
© 2008-2012 IEEE.
PY - 2016/12
Y1 - 2016/12
N2 - In this paper, we report the outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society. As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high resolution RGB images (with a ground sample distance of 5 cm) and a 3-D light detection and ranging point cloud (with a point cloud density of approximatively 65 pts/m2 ). The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this Part B, we report the results obtained by the winners of the 3-D contest, which explored challenging tasks of road extraction and ISO containers identification, respectively. The 2-D part of the contest and a detailed presentation of the dataset are discussed in Part A.
AB - In this paper, we report the outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society. As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high resolution RGB images (with a ground sample distance of 5 cm) and a 3-D light detection and ranging point cloud (with a point cloud density of approximatively 65 pts/m2 ). The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this Part B, we report the results obtained by the winners of the 3-D contest, which explored challenging tasks of road extraction and ISO containers identification, respectively. The 2-D part of the contest and a detailed presentation of the dataset are discussed in Part A.
KW - Image analysis and data fusion (IADF)
KW - light detection and ranging (LiDAR)
KW - multimodal-data fusion
KW - multiresolution-data fusion
KW - multisource-data fusion
KW - object identification
KW - road detection
KW - very high resolution (VHR) data
UR - http://www.scopus.com/inward/record.url?scp=85027417634&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2016.2581843
DO - 10.1109/JSTARS.2016.2581843
M3 - Article
AN - SCOPUS:85027417634
SN - 1939-1404
VL - 9
SP - 5560
EP - 5575
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IS - 12
ER -