Unless otherwise noted, all seminars are held in room 1116 in the Marcus Nanotechnology Building from 12-1 p.m. Seminars are open to the public. Jan-Michael Frahm, Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill, presents Crowd Sourced Fast Scalable Dense Reconstruction of the World.
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 and their depth maps 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.
Jan-Michael Frahm is an Assistant Professor at University of North Carolina at Chapel Hill. He received his PhD in computer vision in 2005 from the Christian-Albrechts University of Kiel, Germany. His Diploma in Computer Science is from the University of Lubeck. Dr. Frahm`s research interests include a variety of computer vision problems. He has worked on structure from motion for single/multi-camera systems for static and dynamic scenes to create 3D models of the scene; real-time multi-view stereo to create a dense scene geometry from camera images; use of camera-sensor systems for 3D scene reconstruction with fusion of multiple orthogonal sensors; improved robust and fast estimation methods from noisy data to compensate for highly noisy measurements in various stages of the reconstruction process; high performance feature tracking for salient image-point motion extraction; and the development of data-parallel algorithms for commodity graphics hardware for efficient 3D reconstruction. He has published over 65 peer reviewed papers in international conferences and journals, and he is Editor in Chief of the Elsevier Journal of Image and Vision Computing.