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Active Visual Object Reconstruction using D-, E-, and T-Optimal Next Best Views
Abstract
In visual 3-D reconstruction tasks with mobile cameras, one wishes to move the cameras so that they provide the views that lead to the best reconstruction result. When the camera motion is adapted during the reconstruction, the view of interest is the next best view for the current shape estimate. We present such a next best view planning approach for visual 3-D reconstruction. The reconstruction is based on a probabilistic state estimation with sensor actions. The next best view is determined by a metric of the state estimation's uncertainty. We compare three metrics: D-optimality, which is based on the entropy and corresponds to the (D)eterminant of the covariance matrix of a Gaussian distribution, E-optimality, and T-optimality, which are based on (E)igenvalues or on the (T)race of this matrix, respectively. We show the validity of our approach with a simulation as well as real-world experiments, and compare reconstruction accuracy and computation time for the optimality criteria.
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Works considering deformable objects and a moving camera commonly reside in active vision and do not address the interaction aspect.
“Works considering deformable objects and a moving camera reside commonly to active vision and do not address the interaction aspect [19], [20], [21], [22].”
From Interactive Perception for Deformable Object Manipulation (2024) · cites this paper as [20]
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Research works printed but not linked: 9
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Cited by
Sorted by citations
Interactive Perception for Deformable Object Manipulation
Weng, Z., Zhou, P., Yin, H., Kravberg, A., Varava, A., Navarro-Alarcon, D., & Kragic, D. (2024) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2024.3431943 · Cited by 7
“Works considering deformable objects and a moving camera reside commonly to active vision and do not address the interaction aspect [19], [20], [21], [22].”
Background
Metadata
- Authors
- Wenhardt, S., Deutsch, B., Angelopoulou, E., & Niemann, H.
- Affiliations
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Venue
- 2007 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2007-06
- Pages
- 1-7
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W1967255195
- Cited by
- 60
- References
- 0
- Citations by year
- 2025: 2 · 2024: 4 · 2023: 2 · 2022: 3 · 2021: 4 · 2020: 4 · 2019: 2 · 2018: 4 · 2017: 5 · 2016: 3 · 2015: 2 · 2014: 4 · 2013: 7 · 2012: 2
- FWCI
- 2.39
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Keywords
- next best view, active vision, 3D reconstruction, smartphone camera, D-optimality, E-optimality, uncertainty measures, probabilistic state estimation, shape estimation
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