26 November, 2019

SS13 – Special Session on Computational Intelligence for Laser-Based Sensing and Measurement


Laser-based sensing and measurement is increasingly used in the industry and many other productive fields, like transportation and surveillance. Computer vision technologies that employ laser in some form or another are widely used in industrial inspection and quality control processes. On the other hand, LiDAR technology has been used for remote sensing with applications in agriculture, forestry and public land management. LiDAR technology has also a prominent role on the emerging transportations systems based on autonomous vehicles in situations that range from personal transportation, to industrial vehicle guidance. Finally, safe LiDAR systems may increasingly be used for surveillance and crowd monitoring in public places because their intrinsic respect for personal data.  Laser based measurements have also a prominent role in the field of flexible manufacturing and additive manufacturing. 

The goal of the special session is to gather researchers working on the application of innovative computational methods, such as deep learning, to the process of laser-generated measurement data for various purposes.


The methods and tools applied to vision and robotics include, but are not limited to, the following:

  • Computational Intelligence methods
  • Machine Learning and Deep Learning methods
  • Self-adaptation and self-organisation
  • Point cloud Registration methods
  • Multimodal information fusion
  • Hardware implementation and algorithms acceleration (GPUs, FPGA,s,…)

The fields of application can be identified, but are not limited to, the following:

  • 3D Scene reconstruction
  • 3D Volume visualization
  • Gesture and posture analysis and recognition
  • Surveillance systems in public areas
  • Autonomous and Social Robots
  • Industry 4.0: inspection and quality control
  • Transportation systems: autonomous navigation and road inventory

Remote sensing: forestry, agriculture, land management

Session Chairs

  • Manuel Graña, University of the Basque Country (Spain)
  • Leyre Torre, University of the Basque Country (Spain)
  • Jose Manuel Lopez-Guede, University of the Basque Country (Spain)
  • Anna Kamińska-Chuchmała, Wroclaw University of Science and Technology (Poland)
  • Marina Aguilar, University of the Basque Country (Spain)


Prof. Manuel Graña

Department of Computer Science, University of the Basque Country (UPV/EHU)

Paseo Manuel de Lardizabal, 1, 20018 San Sebastian (Spain)

e-mail: manuel.grana@ehu.es