MSR Symposium on Computational Photography: “Factored Time-Lapse Video” and “4D Cities: Past, Present, and Future”

Date

July 18, 2007

Speaker

Frank Dellaert and Hanspeter Pfister

Affiliation

Harvard University, College of Computing at Georgia Tech

Overview

Factored Time-Lapse Video – Hanspeter Pfister – Harvard University: In this talk I will describe a method for converting time-lapse photography captured with outdoor cameras into Factored Time-Lapse Video (FTLV): a video in which time appears to move faster (i.e., lapsing) and where data at each pixel has been factored into shadow, illumination, and reflectance components. The factorization allows a user to easily relight the scene, recover a portion of the scene geometry (normals), and to perform advanced image editing operations.
Our method is easy to implement, robust, and provides a compact representation with good reconstruction characteristics. I will show results using several publicly available time-lapse sequences.
4D Cities: Past, Present, and Future – Frank Dellaert – College of Computing at Georgia Tech: The 4D Cities project at Georgia Tech aims at developing techniques to do spatio-temporal reconstruction of urban environments, with applications in virtual tourism, cultural heritage preservation, urban planning and much more. In this project, we start from images taken over a span of 100-150 years and build a 4D model (3D + time) using conventional structure from motion techniques. I will discuss the recent work we presented at CVPR on recovering the ordering of the images from this reconstruction automatically using constraint satisfaction methods. I will also present other ongoing work and future directions, including an exciting planned collaboration with Microsoft research.

Speakers

Frank Dellaert and Hanspeter Pfister

Frank Dellaert is an Assistant Professor at the College of Computing, Georgia Institute of Technology. He graduated in 2001 with a Ph.D. from Carnegie Mellon University. His research focuses on probabilistic methods in Robotics and Computer Vision: he has applied Markov chain Monte Carlo sampling methodologies in a variety of novel settings, most notably to address the correspondence problem in computer vision. Before that, with Dieter Fox and Sebastian Thrun, he has introduced the Monte Carlo localization method for estimating and tracking the pose of robots, which is now a standard and popular tool in mobile robotics. Since coming to Georgia Tech, he explored the theme of probabilistic, model-based reasoning paired with randomized approximation methods in three main research areas: Advanced sequential Monte Carlo methods, Spatio-Temporal Reconstruction from Images, and Simultaneous Localization and Mapping. His homepage can be found at http://www.cc.gatech.edu/~dellaert

Hanspeter Pfister is Gordon McKay Professor of the Practice and Director of Visual Computing at Harvard University. Before that he worked for 11 years at Mitsubishi Electric Research Laboratories (MERL). His research is at the intersection of visualization, computer graphics, and computer vision. He has a Ph.D. in computer science from the State University of New York at Stony Brook. Contact him at hanspeterpfister@harvard.edu.