The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Image Retrieval for Image-Based Localization Revisited
Abstract
To reliably determine the camera pose of an image relative to a 3D point cloud of a scene, correspondences between 2D features and 3D points are needed. Recent work has demonstrated that directly matching the features against the points outperforms methods that take an intermediate image retrieval step in terms of the number of images that can be localized successfully. Yet, direct matching is inherently less scalable than retrieval-based approaches. In this paper, we therefore analyze the algorithmic factors that cause the performance gap and identify false positive votes as the main source of the gap. Based on a detailed experimental evaluation, we show that retrieval methods using a selective voting scheme are able to outperform state-of-the-art direct matching methods. We explore how both selective voting and correspondence computation can be accelerated by using a Hamming embedding of feature descriptors. Furthermore, we introduce a new dataset with challenging query images for the evaluation of image-based localization.
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Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
Video Google: a text retrieval approach to object matching in videos
Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367
DTAM: Dense tracking and mapping in real-time
Newcombe, R. A., Lovegrove, S. J., & Davison, A. J. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126513 · Cited by 2,078 · cited 1×
“With the widespread adoption of mobile camera phones, image-based localization has recently received increased attention as it enables many interesting applications such as mobile landmark recognition [4], real-time camera pose tracking [13, 21, 37], robot navigation [19], or community-based city reconstruction [36].”
BackgroundHamming Embedding and Weak Geometric Consistency for Large Scale Image Search
Jegou, H., Douze, M., & Schmid, C. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-88682-2_24 · Cited by 1,901 · cited 3×
“propose to use Hamming embedding to cast votes only for a subset of all entries in a visual word [14].”
MethodInfluential
Cited by
Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions
Sattler, T., Maddern, W., Toft, C., Torii, A., Hammarstrand, L., Stenborg, E., Safari, D., Okutomi, M., Pollefeys, M., Sivic, J., et al. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00897 · Cited by 699
Self-citationImage matching across wide baselines: From paper to practice
Jin, Y., Mishkin, D., Mishchuk, A., Matas, J., Fua, P., Yi, K. M., & Trulls, E. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01385-0 · Cited by 388
Get Out of My Lab: Large-scale, Real-Time Visual-Inertial Localization
Lynen, S., Sattler, T., Bosse, M., Hesch, J., Pollefeys, M., & Siegwart, R. (2015) · Robotics: Science and Systems XI · doi:10.15607/rss.2015.xi.037 · Cited by 243
Self-citationAttention Weighted Local Descriptors
Wang, C., Xu, R., Lu, K., Xu, S., Meng, W., Zhang, Y., Fan, B., & Zhang, X. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3266728 · Cited by 36
MTLDesc: Looking Wider to Describe Better
Wang, C., Xu, R., Zhang, Y., Xu, S., Meng, W., Fan, B., & Zhang, X. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i2.20138 · Cited by 33
Metadata
- Authors
- Sattler, T., Weyand, T., Leibe, B., & Kobbelt, L.
- Venue
- Procedings of the British Machine Vision Conference 2012
- Publisher
- British Machine Vision Association
- Published
- 2012
- Pages
- 76.1-76.12
- OpenAlex
- W2046166954
- Cited by
- 304
- References
- 6
- FWCI
- 6.15
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Sattler, T., Weyand, T., Leibe, B., & Kobbelt, L. (2012). Image Retrieval for Image-Based Localization Revisited. Procedings of the British Machine Vision Conference 2012. https://doi.org/10.5244/c.26.76
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