Minimal solutions for panoramic stitching given gravity prior
(2021) 18th IEEE/CVF International Conference on Computer Vision, ICCV 2021- Abstract
- When capturing panoramas, people tend to align their cameras with the vertical axis, i.e., the direction of gravity. Moreover, modern devices, e.g. smartphones and tablets, are equipped with an IMU (Inertial Measurement Unit) that can measure the gravity vector accurately. Using this prior, the y-axes of the cameras can be aligned or assumed to be already aligned, reducing the relative orientation to 1-DOF (degree of freedom). Exploiting this assumption, we propose new minimal solutions to panoramic stitching of images taken by cameras with coinciding optical centers, i.e. undergoing pure rotation. We consider six practical camera configurations, from fully calibrated ones up to a camera with unknown fixed or varying focal length and with... (More)
- When capturing panoramas, people tend to align their cameras with the vertical axis, i.e., the direction of gravity. Moreover, modern devices, e.g. smartphones and tablets, are equipped with an IMU (Inertial Measurement Unit) that can measure the gravity vector accurately. Using this prior, the y-axes of the cameras can be aligned or assumed to be already aligned, reducing the relative orientation to 1-DOF (degree of freedom). Exploiting this assumption, we propose new minimal solutions to panoramic stitching of images taken by cameras with coinciding optical centers, i.e. undergoing pure rotation. We consider six practical camera configurations, from fully calibrated ones up to a camera with unknown fixed or varying focal length and with or without radial distortion. The solvers are tested both on synthetic scenes, on more than 500k real image pairs from the Sun360 dataset, and from scenes captured by us using two smartphones equipped with IMUs. The new solvers have similar or better accuracy than the state-of-the-art ones and outperform them in terms of processing time. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/bd99aec6-12bd-472e-814f-b06df04f4bf6
- author
- Ding, Yaqing LU ; Barath, Daniel and Kukelova, Zuzana
- publishing date
- 2021
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- IEEE/CVF International Conference on Computer Vision (ICCV)
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 18th IEEE/CVF International Conference on Computer Vision, ICCV 2021
- conference location
- Virtual, Online, Canada
- conference dates
- 2021-10-11 - 2021-10-17
- external identifiers
-
- scopus:85127758921
- ISBN
- 978-1-6654-2812-5
- 978-1-6654-2813-2
- DOI
- 10.1109/ICCV48922.2021.00553
- language
- English
- LU publication?
- no
- id
- bd99aec6-12bd-472e-814f-b06df04f4bf6
- date added to LUP
- 2022-09-07 17:49:45
- date last changed
- 2024-07-09 08:22:19
@inproceedings{bd99aec6-12bd-472e-814f-b06df04f4bf6, abstract = {{When capturing panoramas, people tend to align their cameras with the vertical axis, i.e., the direction of gravity. Moreover, modern devices, e.g. smartphones and tablets, are equipped with an IMU (Inertial Measurement Unit) that can measure the gravity vector accurately. Using this prior, the y-axes of the cameras can be aligned or assumed to be already aligned, reducing the relative orientation to 1-DOF (degree of freedom). Exploiting this assumption, we propose new minimal solutions to panoramic stitching of images taken by cameras with coinciding optical centers, i.e. undergoing pure rotation. We consider six practical camera configurations, from fully calibrated ones up to a camera with unknown fixed or varying focal length and with or without radial distortion. The solvers are tested both on synthetic scenes, on more than 500k real image pairs from the Sun360 dataset, and from scenes captured by us using two smartphones equipped with IMUs. The new solvers have similar or better accuracy than the state-of-the-art ones and outperform them in terms of processing time.}}, author = {{Ding, Yaqing and Barath, Daniel and Kukelova, Zuzana}}, booktitle = {{IEEE/CVF International Conference on Computer Vision (ICCV)}}, isbn = {{978-1-6654-2812-5}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Minimal solutions for panoramic stitching given gravity prior}}, url = {{http://dx.doi.org/10.1109/ICCV48922.2021.00553}}, doi = {{10.1109/ICCV48922.2021.00553}}, year = {{2021}}, }