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Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion

Open access
Moulon, Pierre, Monasse, Pascal, Marlet, Renaud·2013·2013 IEEE International Conference on Computer Vision

Abstract

Multi-view structure from motion (SfM) estimates the position and orientation of pictures in a common 3D coordinate frame. When views are treated incrementally, this external calibration can be subject to drift, contrary to global methods that distribute residual errors evenly. We propose a new global calibration approach based on the fusion of relative motions between image pairs. We improve an existing method for robustly computing global rotations. We present an efficient a contrario trifocal tensor estimation method, from which stable and precise translation directions can be extracted. We also define an efficient translation registration method that recovers accurate camera positions. These components are combined into an original SfM pipeline. Our experiments show that, on most datasets, it outperforms in accuracy other existing incremental and global pipelines. It also achieves strikingly good running times: it is about 20 times faster than the other global method we could compare to, and as fast as the best incremental method. More importantly, it features better scalability properties.

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Metadata

Authors
Moulon, P., Monasse, P., & Marlet, R.
Venue
2013 IEEE International Conference on Computer Vision
Publisher
IEEE
Published
2013-12
Pages
3248-3255
OpenAlex
W2084613528
Cited by
373
References
35
FWCI
11.52
Type
conference paper
Language
en
Open access
green

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CoChat. (2026). Citation check: Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion. https://app.cochat.ai/papers/10.1109/iccv.2013.403
The paper
Moulon, P., Monasse, P., & Marlet, R. (2013). Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion. 2013 IEEE International Conference on Computer Vision. https://doi.org/10.1109/iccv.2013.403

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