JKU ICG Lab Talk: Jan Kautz, NVIDIA HD

April 14th, 2015, 4:00pm, Computer Science Building (SP 3) room 063 Speaker: Jan Kautz, NVIDIA Title: A Flexible Image Processing Pipeline Abstract: Conventional pipelines for capturing, displaying, and storing images are usually defined as a series of cascaded modules, each responsible for addressing a particular problem. While this divide-and-conquer approach offers many benefits, it also introduces a cumulative error, as each step in the pipeline only considers the output of the previous step, not the original sensor data. We propose an end-to-end system that is aware of the camera and image model, enforces natural image priors, while jointly accounting for common image processing steps like demosaicking, denoising, deconvolution, and so forth, all directly in a given output representation (e.g., YUV, DCT). Our system is flexible and we demonstrate it on regular Bayer images as well as images from custom sensors. In all cases, we achieve large improvements in image quality and signal reconstruction compared to state-of-the-art techniques. About the Speaker: Jan leads the Mobile Visual Computing research team at NVIDIA, working on computational photography and computer vision for mobile devices. Before joining NVIDIA in 2013, Jan was a tenured faculty member at University College London for eight years. He holds a BSc in Computer Science from the University of Erlangen-Nürnberg (1999), an MMath from the University of Waterloo (1999), received his PhD from the Max-Planck-Institut für Informatik (2003), and worked as a post-doc at the Massachusetts Institute of Technology (2003-2006). Jan is particularly interested in computational photography and imaging, computer vision, and computational displays, on which he has published many articles at various conferences including ACM SIGGRAPH, Eurographics, CVPR, ECCV, CHI, and many more.