Capturing vivid 3D models of the world from video
Professor of 3D Computer Vision
Introduction by Professor John Shawe-Taylor, Head of UCL Computer Science
Vote of Thanks by Professor Andrew Zisserman, University of Oxford)
A drinks reception will follow in Roberts Building, Front Foyer
As humans we take the ability to perceive the dynamic world around us in three dimensions for granted. From an early age we can grasp an object by adapting our fingers to its 3D shape; we can understand our mother's feelings by interpreting her facial expressions; or we can effortlessly navigate through a busy street. All of these tasks require some internal 3D representation of shape, deformations and motion.
Building algorithms that can emulate this level of human 3D perception has proved to be a much harder task than initially anticipated. While some degree of success has been achieved when the scene observed by a camera is static or "rigid", inferring the 3D geometry of the vivid moving real world is still in its infancy. This challenge has fascinated Lourdes throughout her research career. In this lecture she will show progress from her early systems which captured sparse 3D models with primitive representations of deformation towards our most recent algorithms which can capture every fold and detail of hands, faces and clothes in 3D using as input video sequences taken with a single consumer camera. There is now great short-term potential for commercial uptake of this technology, and Lourdes will show applications to robotics, augmented and virtual reality and minimally invasive surgery.
Professor Lourdes Agapito obtained her BSc, MSc and PhD (1996) degrees from the Universidad Complutense de Madrid (Spain). She held an EU Marie Curie Postdoctoral Fellowship at The University of Oxford's Robotics Research Group before being appointed as a Lecturer at Queen Mary, University of London in 2001. In 2008 she was awarded an ERC Starting Grant to carry out research on the estimation of 3D models of non-rigid surfaces from monocular video sequences. In July 2013 she joined UCL Computer Science as a Reader (Associate Professor) where she leads a research team that focuses on 3D dynamic scene understanding from video.
Lourdes is Program Chair for CVPR 2016, the top annual conference in computer vision; in addition she was Programme Chair for 3DV'14 and Area Chair for CVPR'14, ECCV'14, ACCV'14 and Workshops Chair for ECCV'14. She has been keynote speaker for CVMP'15 and for several workshops associated with the main computer vision conferences (ICCV, CVPR and ECCV). Lourdes is Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), a member of the Executive Committee of the British Machine Vision Association and a member of the EPSRC Peer Review College.