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Torsten Sattler “Image-Based Localization at Large and on Small Devices”

December 6, 2016 @ 11:00 am - 12:00 pm

Torsten Sattler
Senior Researcher, ETH Zurich

Image-Based Localization at Large and on Small Devices

Tuesday, December 6, 2016
FB141, 11:00 a.m.


Image-based localization is the problem of determining the exact position and orientation of a camera based on an image. It is encountered in numerous applications such as self-driving cars and other autonomous vehicles, robotics, Structure-from-Motion, Augmented / Mixed / Virtual Reality, and any scenario requiring to localize and staying localized in an environment based on camera data. The image-based localization problem is typically solved by establishing 2D-3D matches between pixels in a camera image and points in a 3D model of the scene, followed by estimating the camera pose from these matches. After briefly introducing the standard pipeline, we mostly focuses on two variants of the localization problem: Localization at a large, e.g., city, scale and real-time localization on mobile devices.

The first part of the talk focuses on problems of large-scale localization: Feature matching becomes harder due to globally repeating structures, while geometric configurations become less distinctive at the same time. Consequently, advanced metrics need to be developed in order to decide with high precision whether an image has been localized successfully.

The second part of the talk concentrates on enabling localization on mobile devices. We show how real-time camera pose tracking can be combined with non real-time localization techniques to adhere to the limited computational capabilities of mobile devices such as tablets or smart phones. In addition, we demonstrate how client-server architectures and compression schemes can be used to handle the memory restrictions of such devices.

The talk concludes with a overview over interesting open challenges, including some example scenarios where classical feature matching methods fail.

Speaker Bio

Torsten Sattler received a PhD in Computer Science from RWTH Aachen University, Germany, in 2013 under the supervision of Bastian Leibe and Leif Kobbelt. In December 2013, he joined the Computer Vision and Geometry Group (CVG) of Prof. Marc Pollefeys at ETH Zurich, Switzerland, where he currently is a senior researcher. His research interests include (large-scale) image-based localization using Structure-from-Motion point clouds, real-time localization and SLAM on mobile devices, image retrieval and efficient spatial verification, camera calibration and pose estimation, and Structure-from-Motion. Torsten has worked on dense sensing for self-driving cars as part of the V-Charge project. He is currently involved in enabling semantic SLAM and re-localization for gardening robots and is contributing to Google’s Tango project, where he leads CVG’s research efforts.

Faculty Host: Jan-Michael Frahm (frahm@cs.unc.edu)


December 6, 2016
11:00 am - 12:00 pm
Event Categories:


141 Brooks Building (FB141)
Brooks Computer Science Building, S. Columbia St.
Chapel Hill, NC 27599 United States
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