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Center for Nonlinear Studies |
In recent years photo and video sharing web sites like Flickr and Youtube have become increasingly popular. Nowadays, every day millions of photos are uploaded. These photos survey the world. Given the scale of data we are facing significant challenges to process them within a short time frame given limited resources. In my talk I will present my work on the highly efficient organization and reconstruction of 3D models from city scale photo collections (millions of images per city) on a single PC in the span of a day as well as my work on the real-time scene reconstruction from video. The approaches address a variety of the current challenges to achieve a concurrent 3D model from these data. For reconstruction from photo collections these challenges are: selecting the data of interest from the noisy datasets, efficient robust camera motion estimation. Shared challenges of photo collection based 3D modeling and 3D reconstruction from video are: high performance stereo estimation from multiple views, as well as image based location recognition for topology detection. In the talk I will discuss the details of our appearance and geometry based image organization method, our efficient stereo technique for determining the scene depths from photo collection images will also be explained during the talk. It allows to perform the scene depth estimation with multiple frames per second from a large set of views with a considerable variation in appearance. Additionally, I will discuss some of the lessons learned for how to approach these large scale challenges in the future.
Host: Alexei N. Skurikhin, MS D436, Space & Remote Sensing Group, Los Alamos National Laboratory, 667-5067