Dr. Simon Lucey
Associate Research Professor
Robotics Institute, Carnegie Mellon University
Friday, April 28, 2017
11 AM - 12 PM
Mobile devices are shifting from being a tool for communication to one that is used increasingly for perception. In this talk we will discuss my group's work in the rapidly emerging space of using mobile devices to visually sense the 3D world. First, we will discuss the employment of high-speed (240+ FPS) cameras, now found on most consumer mobile devices. In particular, we will discuss how these high frame rates afford the application of direct photometric methods that allow for - previously unattainable - accurate, dense, and computationally efficient camera tracking & 3D reconstruction. Second, we will discuss how the problem of object category specific dense 3D reconstruction (e.g. "chair", "bike", "table", etc.) can be posed as a Non-Rigid Structure from Motion (NRSfM) problem. We will discuss some theoretical advancements we have made recently surrounding this problem - in particular when one assumes the 3D shape being reconstructed is compressible. We will then relate these theoretical advancements to practical algorithms that can be applied to most modern mobile devices.
Simon Lucey is an Associate Research Professor
within the Robotics Institute at Carnegie Mellon University. Prior
to this he was an Australian Research Council (ARC) Future Fellow
(2009-2013) and a Principal Research Scientist at Australia's
national science agency the Commonwealth Scientific and Industrial
Research Organisation (CSIRO). Simon leads the CI2CV laboratory
(www.cs.cmu.edu/~CI2CV), one of the leading groups in the world for mobile computer vision - the group explores problems that intersect between signal processing, computer vision and machine learning. He received his Ph.D. in 2003 from the Queensland University of Technology, Australia. To his credit he has over 100 peer reviewed publications. He has served as Area Chair for conferences like CVPR, ACCV, F&G, and ICPR. He has organized and chaired numerous workshops, tutorials and summer schools in both the Computer Vision and Machine Learning communities. He has also previously served as Associate Editors for both the IEEE Trans. on Affective Computing & the IEEE Trans. on Multimedia.
Dr. Xiaoming Liu