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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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18.01.2021

Yaron Lipman (Weizmann Institute of Science) will give a talk in the TUM AI lecture series on Jan 21st, 3pm! Livestream

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

More


Large-Scale Direct SLAM for Omnidirectional Cameras

We propose a real-time, direct monocular SLAM method for omnidirectional or wide field-of-view fisheye cam- eras. Both tracking (direct image alignment) and mapping (pixel-wise distance filtering) are directly formulated for the unified omnidirectional model, which can model central imaging devices with a field of view well above 150° . This is in stark contrast to existing direct mono-SLAM approaches like DTAM or LSD-SLAM, which operate on rectified images, limiting the field of view to well below 180° . Not only does this allow to observe – and reconstruct – a larger portion of the surrounding environment, but it also makes the system more robust to degenerate (rotation-only) movement. The two main contribution are (1) the formulation of direct image alignment for the unified omnidirectional model, and (2) a fast yet accurate approach to incremental stereo directly on distorted images. We evaluated our framework on real-world sequences taken with a 185◦ fish-eye lens, and compare it to a rectified and a piecewise rectified approach.

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Unless stated otherwise, all data in the SLAM for Omnidirectional Cameras Dataset is licensed under a Creative Commons 4.0 Attribution License (CC BY 4.0).

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Conference and Workshop Papers
2015
[]Large-Scale Direct SLAM for Omnidirectional Cameras (D. Caruso, J. Engel and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2015.  [bibtex] [pdf] [video]
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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group

News

18.01.2021

Yaron Lipman (Weizmann Institute of Science) will give a talk in the TUM AI lecture series on Jan 21st, 3pm! Livestream

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

More