Instructor: Claudio Greco, DXOMARK
Level: Intermediate
Prerequisites: Fundamentals of image processing and camera inner working

Benefits:
This course enables the attendee to:

• Identify the most important image quality attributes for computer vision.
• Understand the problems encountered when testing a real device in a lab and how to approach them.
• Understand which influencing factor one needs to address for each measurement.
• See a real-life measurement setup and how to control it.
• Talk with experts who have participated in the standardization of the metrics and the development of the equipment.

Course Description:
The purpose of this course is to give a short overview of what to measure and how to measure it in terms of image quality for computer vision. An automotive application is the case study of focus. Several aspects of typical automotive systems make them very challenging to measure, more so than the consumer imaging systems to which most people are accustomed. In fact, when designing such a measurement, one is quickly confronted with two main aspects: a much wider dynamic range than most consumer imaging systems and a much larger field of view.

The course describes how the definition and measurement setup and protocols of even well-known metrics (such as noise) needed to be extended to cope with new factors in the new IEEE/P2020 standard. Half the the course is dedicated to the practical challenges and solutions involved in making an accurate measurement in a laboratory. The IEEE/P2020 setups are present in the room. Attendees are given an overview of all the influencing factors to take into account for each measurement.

Intended Audience: Image scientists, engineers, or managers who wish to learn more about image quality for computer vision.

Claudio Greco received his BEng and MSc from the University of Naples "Federico II" and a PhD in signal and image processing from the “École Nationale Supérieure des Télécommunications” (now Telecom Paris). After a few years in academia, he joined DXOMARK first as a senior image science engineer, then as technical lead, and currently as image science director.Greco has published numerous articles in top-tier scientific journals and has been a keynote speaker at several international conferences. His research interests include objective no-reference image quality evaluation in applications such as mobile photography, automotive, medical imaging, and defense.