Torsten Sattler presents Challenges in Long-Term Visual Localization

On 2018-07-24 11:00:00 at CIIRC Seminar. Room B-670 (Building B, the 6th floor), Jugoslavskych partyzanu 3
*** CIIRC Seminar. Room B-670 (Building B, the 6th floor), Jugoslavskych
partyzanu 3 ***

Visual localization is the problem of estimating the position and orientation
from which an image was taken with respect to a 3D model of a known scene. This
problem has important applications, including autonomous vehicles (including
self-driving cars and other robots) and augmented / mixed / virtual reality.
While multiple solutions to the visual localization problem exist both in the
Robotics and Computer Vision communities for accurate camera pose estimation,
they typically assume that the scene does not change over time. However, this
assumption is often invalid in practice, both in indoor and outdoor
environments. This talk thus briefly discusses the challenges encountered when
trying to localize images over a longer period of time. Next, we show how a
combination of 3D scene geometry and higher-level scene understanding can help
to enable visual localization in conditions where both classical and recently
proposed learning-based approaches struggle.

researcher and Marc Pollefeys’ deputy while Prof. Pollefeys is on leave from
stereo, image retrieval and efficient spatial verification, camera calibration
project where he leads the efforts on a workpackage), research for Google’s
Tango project, where he leads CVG’s research efforts, and in work on
self-driving cars.
Responsible person: Petr Pošík