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Members: FreeRAS
IEEE Members: Free
Non-members: FreeLength: 00:29:01
30 May 2017
Video Description
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. In this session, I will show progress from early systems which captured sparse 3D models with primitive representations of deformation towards the most recent algorithms which can capture every fold and detail of hands or faces 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 I will show applications to robotics, augmented and virtual reality and minimally invasive surgery.
ICRA 2017
The 2017 IEEE International Conference on Robotics and Automation (ICRA) was held from May 29 to June 3, 2017 at Sands Expo and Convention Centre, Marina Bay Sands in Singapore. ICRA is IEEE Robotics and Automation Society's flagship conference and is a premier international forum for robotics researchers to present their work. The conference theme, “Innovation, Entrepreneurship, and Real-world Solutions”, underscores the need for innovative R&D talent, dynamic and goal-driven entrepreneurs and practitioners using robotics and automation technology to solve challenging real-world problems such as shortage of labour, an ageing society, and creating sustainable environments.
Speaker
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 the Department of Computer Science at University College London (UCL) as a Reader where she leads a research team that focuses on 3D dynamic scene understanding from video and became full Professor of 3D Computer Vision in 2015.
Lourdes was 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) and the International Journal of Computer Vision (IJCV), a member of the Executive Committee of the British Machine Vision Association and a member of the EPSRC Peer Review College.
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. In this session, I will show progress from early systems which captured sparse 3D models with primitive representations of deformation towards the most recent algorithms which can capture every fold and detail of hands or faces 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 I will show applications to robotics, augmented and virtual reality and minimally invasive surgery.
ICRA 2017
The 2017 IEEE International Conference on Robotics and Automation (ICRA) was held from May 29 to June 3, 2017 at Sands Expo and Convention Centre, Marina Bay Sands in Singapore. ICRA is IEEE Robotics and Automation Society's flagship conference and is a premier international forum for robotics researchers to present their work. The conference theme, “Innovation, Entrepreneurship, and Real-world Solutions”, underscores the need for innovative R&D talent, dynamic and goal-driven entrepreneurs and practitioners using robotics and automation technology to solve challenging real-world problems such as shortage of labour, an ageing society, and creating sustainable environments.
Speaker
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 the Department of Computer Science at University College London (UCL) as a Reader where she leads a research team that focuses on 3D dynamic scene understanding from video and became full Professor of 3D Computer Vision in 2015.
Lourdes was 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) and the International Journal of Computer Vision (IJCV), a member of the Executive Committee of the British Machine Vision Association and a member of the EPSRC Peer Review College.
