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The recovering of our 3D-world with only one camera is a challenge in many fields ranging from self-driving cars to plastic surgery. In this video DANIEL CREMERS presents innovations from computer vision to tackle that challenge. Modelling the movement of a camera in addition to the geometry of the depicted world and using new algorithms allow the recovery of more pictures in real-time. The algorithms compute the highest possible consistency between consecutive images and make it possible to recover even moving objects with the limited computational space of a laptop.


Daniel Cremers is Professor for Computer Science and Mathematics at the Technical University Munich. As a postdoctoral researcher, Cremers spent two years at the University of California, Los Angeles and one year as a Siemens Corporate researcher at Princeton, New Jersey.

For his research in the field of computer vision and mathematical image analysis, Cremers was awarded the esteemed Leibniz Award 2016. Cremers seeks to tackle the difficulty of representing a 3-dimensional world on camera.


Technical University of Munich (Technische Universität München)

"Technische Universität München (TUM) is one of Europe’s top universities. It is committed to excellence in research and teaching, interdisciplinaryeducation and the active promotion of promising young scientists. The university also forges strong links with companies and scientific institutionsacross the world. TUM was one of the first universities in Germany to be named a University of Excellence. Moreover, TUM regularly ranks among the best European universities in international rankings." ( Source )
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Original publication

LSD-SLAM: Large-Scale Direct Monocular SLAM

Engel Jakob, Schöps Thomas and Cremers Daniel
Computer Vision–ECCV 2014
Published in 2014

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