MSR Symposium on Computational Photography – Removing Camera Shake from a Single Photograph, Object Movies, Photosynth, and other Cool Stuff, and Some Further Thoughts on Computational Photography


July 18, 2007


Drew Steedly, Aaron Hertzmann, and Noah Snavely


University of Toronto, Microsoft Research


Removing Camera Shake from a Single Photograph; Aaron Hertzmann – University of Toronto: Camera shake during exposure leads to objectionable image blur and ruins many photographs. Conventional blind deconvolution methods typically assume frequency domain constraints on images, or overly simplied parametric forms for the motion path during camera shake. Real camera motions can follow convoluted paths, and a spatial domain prior can better maintain visually salient image characteristics. We introduce a method to remove the effects of camera shake from seriously blurred images. The method assumes a uniform camera blur over the image, negligible in-plane camera rotation, and no blur due to moving objects in the scene. The user must specify an image region without saturation effects. I’ll discuss issues in this blind deconvolution problem, and show results for a variety of digital photographs. Joint work with Rob Fergus, Barun Singh, Sam Roweis, and Bill Freeman.

Object Movies, Photosynth, and other Cool Stuff; Noah Snavely, Drew Steedly – Microsoft Research: Photo Tourism and Photosynth have generated a lot of excitement as a new way to interactively visualize and navigate a collection of photographs situated in three dimensions. In this talk, we present some recent developments in our research. First, we show how by interactively manipulating viewpoints while automatically selecting the next image, we can achieve the fluidity of control and three-dimensionality inherent in *object movies*. Second, we show how three-dimensional models can be reconstructed from large uncontrolled collections of images. Finally, we discuss different approaches for dealing with large sets of data. We also present some recently reconstructed models from Korea and England.


Drew Steedly, Aaron Hertzmann, and Noah Snavely

Drew Steedly is a PhD Candidate in the College of Computing, Georgia Institute of Technology, where his research focuses on efficient techniques for generating 3D reconstructions of large environments from video. He joined the Georgia Tech GVU Center’s Computational Perception Lab in 1998 where he is working with Professor Irfan Essa and hopes to complete his dissertation in Summer of 2004. He received a B.S. in Electrical Engineering from the University of Florida in 1994. He earned his M.S. in Electrical and Computer Engineering from Georgia Tech in 1995 with a focus in analog IC design. After his M.S. he worked at Integrated Device Technology designing integrated circuits and developing design methodologies, where he still consults and helps with various design projects. Drew was a recipient of the 2001-2002 Intel Foundation Graduate Fellowship.

Aaron Hertzmann is an Assistant Professor of Computer Science at University of Toronto. He received a BA in Computer Science and Art & Art History from Rice University in 1996, and an MS and PhD in Computer Science from New York University in 1998 and 2001, respectively. In the past, he has worked at University of Washington, Microsoft Research, Mitsubishi Electric Research Lab, Interval Research Corporation and NEC Research Institute. He serves as an Associate Editor for IEEE Transactions on Visualization and Computer Graphics, served as an Area Coordinator for SIGGRAPH 2007, and co-chaired NPAR 2004. His awards include an MIT TR100 (2004), a Ontario Early Researcher Award (2005), a Sloan Foundation Fellowship (2006), and a Microsoft New Faculty Fellowship (2007). His research interests include computer vision, computer graphics, and machine learning.

Noah Snavely is a Ph.D. candidate in the Graphics and Imaging Laboratory (GRAIL) of the Department of Computer Science and Engineering at the University of Washington, advised by Steven Seitz and Richard Szeliski. His research interests span computer vision, computer graphics, and interactive techniques, and his thesis research has focused on 3D reconstruction and visualization of large, diverse photo collections. He expects to complete his Ph.D. in the summer of 2008. He is the recipient of a National Science Foundation fellowship (2003) and a Microsoft Live Labs fellowship (2007).