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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

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Informatik IX
Computer Vision Group

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

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News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

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research:vslam:double-sphere [2018/08/20 17:17]
usenko
research:vslam:double-sphere [2018/08/20 17:18]
usenko
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 done done
 </code> </code>
- 
-**Note:** Kalibr fails to calibrate pinhole-equi on the TUMVI calibration sequence, which might be a limitation of the way this is implemented in Kalibr. First, Kalibr implements Kannala-Brandt (which corresponds to pinhole-equi in Kalibr) as pinhole+distortion, which limits it to below 180 deg, where this lens is around 190 deg FOV. Second, Kalibr does initialization by optimizing with a single image, which may result in divergence when the parameters are not well constrained by a single image. We found with our own calibration tool that the Kanala-Brandt model can fit this lens quite well. 
  
 Example of camera calibration for the Double Sphere paper dataset ({{ :research:vslam:double-sphere:ds_results.zip |results}}): Example of camera calibration for the Double Sphere paper dataset ({{ :research:vslam:double-sphere:ds_results.zip |results}}):
Line 221: Line 219:
 done done
 </code> </code>
 +
 +**Note:** Kalibr fails to calibrate pinhole-equi on the TUMVI calibration sequence, which might be a limitation of the way this is implemented in Kalibr. First, Kalibr implements Kannala-Brandt (which corresponds to pinhole-equi in Kalibr) as pinhole+distortion, which limits it to below 180 deg, where this lens is around 190 deg FOV. Second, Kalibr does initialization by optimizing with a single image, which may result in divergence when the parameters are not well constrained by a single image. We found with our own calibration tool that the Kanala-Brandt model can fit this lens quite well.
  

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Informatik IX
Computer Vision Group

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

Follow us on:

News

04.03.2024

We have twelve papers accepted to CVPR 2024. Check our publication page for more details.

18.07.2023

We have four papers accepted to ICCV 2023. Check out our publication page for more details.

02.03.2023

CVPR 2023

We have six papers accepted to CVPR 2023. Check out our publication page for more details.

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022. Check out our publication page for more details.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023. Check out our publication page for more details.

More