Computer vision is one the core research fields of the Visual Computing section at DTU Compute. We aim to develop fundamental methods that allow for fast and accurate detections and measurments of the real world. Our focus area spans all of object geometry, optical properties, lighting environments, as well as sub-resolution micro-geometry. We want to be able to record the full digital twin of a natural scene by taking into account the interactions between light and material. Our highlights include 3D scanning, Acquisition of surface BRDFs, and Seeing transparency.
3D scanning
Low-cost sensors such as Microsoft Kinect and time of flight cameras have made the 3D sensor ubiquitous and have resulted in a vast amount of new applications and methods. However, such low-cost sensors are generally limited in their accuracy and precision, making them unsuitable for problems such as precise tracking and pose estimation. With recent improvements in projector technology, increased processing power, and new method developments with central contributions from our research group, it is now possible to perform faster and highly accurate structured light scans. This offers new opportunities for studying dynamic scenes, quality control, human-computer interaction and more.