The Internet has become a massive source of photographic imagery. Billions of photos are available from sources ranging from Google Maps to Flickr, and myriad views of virtually every famous location on Earth are readily available. For instance, a Google Image search for "Eiffel Tower" returns almost half a million images, and a search for " Grand Canyon " returns nearly three million photos, representing many different photographers, viewpoints, times of day, weather conditions, and seasons. While extremely rich, these vast, unorganized photo collections are difficult to explore and search through using traditional photo browsing tools.
In this talk, I will present my work on new computer vision techniques for recovering the 3D structure of scenes from very large, diverse photo collections, and on new visualization techniques for exploring these reconstructed scenes in 3D. I will first describe Photo Tourism, an approach for navigating through photos using geometric controls. I will then discuss more recent work in creating simple, intuitive navigation interfaces by analyzing patterns in how people take photographs, and using these patterns to derive optimized 3D controls for each scene.
Noah Snavely is a Ph.D. candidate in the Department of Computer Science and Engineering at the University of Washington , advised by Professor Steven Seitz and Dr. Richard Szeliski. His research interests span computer vision, computer graphics, and interactive techniques. He is particularly interested in developing new computer vision algorithms for the analysis of large, diverse photo collections, and on leveraging these algorithms to produce effective visualizations of scenes. He is the recipient of a National Science Foundation fellowship (2003) and a Microsoft Live Labs fellowship (2007).