Special Session 12

RGB-D sensors, combining both video- and depth-based sensing capabilities, can facilitate several applications, like the detection and understanding of human movements, actions and activities, and the interactions between humans and surrounding environment and objects. The joint availability of synchronized video signals and depth measurement information, from easy-to-use and low-cost sensors, helps to improve the performance of automatic classification and recognition algorithms, supporting crucial processes such as the extraction of skeletal joints and human silhouette, with increased accuracy and reducing their dependence from shadows, light reflections and color similarity.
This Special Session aims to promote research contributions on RGB-D sensors as measurement devices applied in the context of Industry 4.0, focusing on the characterization and assessment of their performance in different operating conditions, especially related to challenging deployments “in the wild”. How the quality and reliability of the measured data influence the performance of machine learning approaches is of utmost interest, as well as the investigation of new and innovative research ideas in which RGB-D sensors may provide a basic contribution. New theoretical approaches, experimental tests, and assessment in real-world use cases, are of interest.

Submissions are welcomed on (but not limited to):

• RGB-D based measurements in Industry4.0
• Vision and Depth system-based Robotics and Smart Manufacturing
• Innovative calibration methods
• Deep Learning based applications using RGB-D measurement data
• RGB-D and wearable sensors fusion
• RGB-D based contactless measurement systems
• Metrological characterization of RGB- D sensors for human monitoring
• RGB-D based applications for the monitoring of human-robot interactions
• Metrics, algorithms and signal processing techniques
• Innovative applications of RGB-D sensors and practical solutions
• Reliability, validity, and accuracy of RGB-D sensors and measuring systems

Susanna Spinsante is currently a Tenure Track Assistant Professor in Electrical and Electronic Measurements at the Information Engineering Department (DII) of Università Politecnica delle Marche. She received her PhD in Electronics and Telecommunications Engineering in 2005 from the same University, where she spent several years working in signal processing for telecommunications and video applications. Since 2012 her research interests are focused on the use of RGB-D sensors for the extraction of measurement signals applied to human monitoring, motion-related measurements, action recognition, and Active and Assisted Living. She co-authored more than 190 papers in international peer reviewed journals and conference proceedings. She currently leads a DII Research Unit in two co-funded projects, from AAL JP and MYBL JP, focused on the use of RGB-D and wearable sensors for human lifelogging and action understanding. She is a Senior Member of the IEEE since 2013, member of the IEEE Instrumentation and Measurement Society, IEEE Signal Processing Society, GMEE, and CNIT. She is currently the Chair of the “RGB-D Sensors” technical committee of the IEEE Sensors Italy Chapter.

Cristina Nuzzi is a Ph. D student in Applied Mechanics at the University of Brescia, Italy, since 2017. She received both the B.S. degree and the M. S. degree in Industrial Automation Engineering in 2015 and 2017 respectively from the University of Brescia, Italy. She is a member of the group of Vision Systems for Mechatronics lead by Prof. Giovanna Sansoni. Her research interests include vision systems and deep learning solutions for Robotics and Smart Manufacturing.

Simone Pasinetti received the B.S. degree and the M.S. degree (with honors) in Automation Engineering from University of Brescia, Brescia, Italy, in 2009 and 2011 respectively, with a thesis concerning the control of mechanical actuators with SEMG signals. He received the Ph. D. degree in applied mechanics from University of Brescia, Brescia, Italy, in 2015 with a thesis titled “Development of measurement protocols for the analysis of the functional evaluation and rehabilitation, in biomechanics field”. During the Ph. D. he had in contact with the Institute of Intelligent Systems and Robotics (ISIR), Paris, France, where he carried out research concerning the dynamic posture analysis. Since January 2015, he has been a research fellow for the Laboratory of Vision Systems for Mechatronics (Vis4Mechs) in the Department of Mechanical and Industrial Engineering at University of Brescia, Brescia, Italy. He is currently working on posture and gait analysis, depth sensors, collaborative robotics, 2D and 3D vision systems development. His research interests include biomechanics of human posture, motion analysis, EMG analysis, collaborative robotics and 2D and 3D vision systems.