Novel Methods and Applications of 3D Data Processing

Dear Colleagues,

In the last decade, the appearance of cheap depth sensors on the market has allowed researchers to experiment using 3D and RGB-D cameras, developing novel perception algorithms and methods.
Ten years later, research fields such as augmented reality and robotics have been transformed by the availability of 3D information. The processing of 3D data is becoming almost as ubiquitous as 2D machine vision. Moreover, depth sensors are being successfully applied in industries, entertainment, and cultural heritage.
As 3D data is often copiously available, it needs to be interpreted, merged, and processed in a consistent way, guaranteeing accuracy and efficiency. Due to the abundance of such 3D data, issues have arisen relating to storage and visualization. Furthermore, many common methods of 2D computer vision, up to convolutional neural networks, strongly depend on input data structure and have to be reworked and adapted for 3D perception.
This Special Issue is dedicated to novel achievements in the field of 3D and RGB-D sensor data processing in any form. Topics of interest include but are not limited to the following:

• 3D perception
• 3D reconstruction
• Sensor fusion
• Sensor tracking and pose estimation
• Mapping and SLAM
• Segmentation, object detection, and recognition from 3D data
• Active perception, viewpoint optimization, and next best view planning
• Robotic 3D perception
• Processing of large scale 3D datasets
• Computational geometry for 3D data
• Deep learning and convolutional neural networks for 3D data
• Visualization of 3D information
• 3D sensors for virtual and augmented reality
• 2D/3D machine vision for industrial applications

Dr. Riccardo Monica
Prof. Jacopo Aleotti
Guest Editors

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• 3D perception
• 3D reconstruction
• Active perception
• 3D data processing
• 3D visualization