ISPRS Journal of Photogrammetry and Remote Sensing Theme Issue “Point Cloud Processing”

in Special Issue   Posted on August 11, 2017 

Information for the Special Issue

Special Issue Call for Papers:

Guest Editors:

Ruisheng Wang (University of Calgary, Canada)
Bisheng Yang (Wuhan University, China)
Florent Lafarge (INRIA, France)
Suya You (University of Southern California, USA)

Submission deadline: Sep 5 2017
Planned publication date: Summer 2018

Over the past few decades, point clouds from LiDAR (light detection and ranging) and passive imaging technologies have been major data sources for mapping applications in the photogrammetry and remote sensing communities. In recent years, processing large-scale geospatial data, especially point clouds, has also drawn considerable attention from the computer vision, computer graphics and robotics communities. Workshops in recent premier computer vision and graphics conferences, such as the workshop on point cloud processing in computer vision at CVPR (computer vision and pattern recognition) 2012 and IQmulus workshop on processing large geospatial data at SGP (symposium on geometry processing) 2014, were focused on point cloud processing. Several ISPRS conference events, such as the 2014 Photogrammetric Computer Vision Symposium, have also placed an emphasis on point cloud processing. The purpose of this theme issue is to increase interdisciplinary interaction and collaboration in point cloud processing among photogrammetry, computer vision, computer graphics (geometry processing and geometric modeling), and robotics.  

This theme issue covers a range of topics on point clouds generated from LiDAR and various image sources. Georeferenced point clouds collected from different platforms such as aircraft, UAV (unmanned aerial vehicles), vehicle, terrestrial scanning, hand-held devices, and backpacks of indoor and outdoor scenes, are particularly relevant to this theme issue. Point clouds generated from images such as aerial images, satellite imagery, street view panoramas, and camera phone images are also of relevance. The topics range from low-level processing to high-level understanding including feature extraction, segmentation, recognition, and modeling. The list of suggested topics includes but is not limited to:

  • Deep learning for point cloud processing
  • Point clouds from stereo, panoramas, camera phone images, oblique and satellite imagery
  • Point cloud registration and segmentation
  • High performance computing for large-scale point clouds
  • 3D object recognition, classification, and change detection
  • Large-scale urban modeling from aerial and mobile LiDAR
  • 2D floorplan generation and 3D modeling of indoor point clouds
  • Fusion of images and point clouds for semantic segmentation
  • Industrial applications with large-scale point clouds
  • Rendering and visualization of large-scale point clouds

The theme issue seeks high-quality research and application submissions in all aspects of 3D point cloud processing. Test on Benchmark datasets are strongly encouraged. Papers must be original contributions, not previously published or submitted to other journals. Submissions based on previous published or submitted conference papers may be considered provided they are considerably improved and extended. Papers must follow the instructions for authors at

Submit your manuscript to  by September 5, 2017.  

Prof. Ruisheng Wang
Department of Geomatics Engineering
University of Calgary, Canada
[email protected]

Prof. Bisheng Yang
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing
Wuhan University, China
[email protected]

Dr. Florent Lafarge
Titane research group
INRIA, France
[email protected]

Prof. Suya You
The Computer Graphics and Immersive Technologies (CGIT) laboratory
University of Southern California, USA
[email protected]

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