3DS Smart Cities – 3D Sensing for Smart Cities

High-accuracy and high-efficiency 3D sensing and associated data processing techniques are urgently needed for smart cities. 3D geospatial data acquired by digital photogrammetry and LiDAR systems have become one of the most important data sources to support smart city applications, such as city infrastructure inventory, city planning, urban design, autonomous driving, etc. This workshop will seek contributions covering advanced topics related to the state of the art and future trends of 3D sensing technology and algorithms for smart city applications. Papers addressing the following topics are welcome: photogrammetric mapping, LiDAR point cloud processing, ubiquitous sensing, cross-modality sensing, etc. The workshop will be part of the ISPRS Geospatial Week 2023 hosted by the Arab Academy for Science, Technology, and Maritime Transport (AASTMT) in parallel with several related geospatial workshops.

Themes of event:

• Airborne photogrammetric mapping for smart cities

• Airborne LiDAR point cloud processing for smart cities

• Mobile LiDAR point cloud processing for smart cities

• UAS-based photogrammetric mapping for smart cities

• UAS borne LiDAR point cloud processing for smart cities

• Deep learning methods for smart cities

• Low-cost multi-sensor systems for smart cities

• Multi-sensor system design and on-board processing

• Cross-modality sensing data integration

• Ubiquitous sensing with sensors in mobile devices

• Sensor fusion in support of smart city applications

• Place recognition and localization for smart cities

Scientific Committee:

• Andrea Lingua, Polytechnic University of Turin, Italy

• Jiaojiao Tian, German Aerospace Center (DLR), Germany

• Andrea Masiero, University of Florence, Italy

• Rongjun Qin, Ohio State University, USA

• Bisheng Yang, Wuhan University, China

• Jonathan Li, University of Waterloo, Canada

• Cheng Wang, Chinese Academy of Sciences, China

• Chun Liu, Tongji University, China

• Jinha Jung, Purdue University, USA

• Yan Xia, Technical University of Munich, Germany