GeoGlue: feature matching with self-supervised geometric priors for high-resolution UAV images

References

• Akinlar, C., and C. Topal. 2011. “EDLines: A Real-Time Line Segment Detector with a False Detection Control.” Pattern Recognition Letters 32 (13): 1633–1642. doi:10.1016/j.patrec.2011.06.001.
   Web of Science ®Google Scholar
• Ballard, D. 1981. “Generalizing the Hough Transform to Detect Arbitrary Shapes.” Pattern Recognition 13: 111–122. doi:10.1016/0031-3203(81)90009-1
   Web of Science ®Google Scholar
• Bay, H., A. Ess, T. Tuytelaars, and L. Van Gool. 2008. “Speeded-Up Robust Features (SURF).” Computer Vision and Image Understanding 110: 346–359. doi:10.1016/j.cviu.2007.09.014.
   Web of Science ®Google Scholar
• Bertasius, G., J. Shi, and L. Torresani. 2015. “DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection.” 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, IEEE, 4380–4389. doi:10.1109/CVPR.2015.7299067.
   Google Scholar
• Calonder, M., V. Lepetit, C. Strecha, and P. Fua. 2010. “Brief: Binary Robust Independent Elementary Features.” The 11th European Conference on Computer Vision (ECCV), Heraklion, Crete, Greece, Springer-Verlag, 778–792. doi:10.5555/1888089.1888148.
   Google Scholar
• Canny, J. 1986. “A Computational Approach to Edge Detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 679–698. doi:10.1109/TPAMI.1986.4767851.
   PubMed Web of Science ®Google Scholar
• Cipolla, R., Y. Gal, and A. Kendall. 2018. “Multi-task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics.” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Lake City, UT, USA, IEEE, 7482–7491. doi:10.1109/CVPR.2018.00781.
   Google Scholar
• Cover, T., and P. Hart. 1967. “Nearest Neighbor Pattern Classification.” IEEE Transactions on Information Theory 13: 21–27. doi:10.1109/TIT.1967.1053964.
   Web of Science ®Google Scholar
• Cristina, S.-C., and S. Holban. 2013. “A Comparison of X-Ray Image Segmentation Techniques.” Advances in Electrical and Computer Engineering 13: 85–92. doi:10.4316/AECE.2013.03014.
   Web of Science ®Google Scholar
• de Lima, R., A. A. Cabrera-Ponce, and J. Martinez-Carranza. 2021. “Parallel Hashing-Based Matching for Real-Time Aerial Image Mosaicing.” Journal of Real-Time Image Processing 18: 143–156. doi:10.1007/s11554-020-00959-y.
   Web of Science ®Google Scholar
• de Lima, R., and J. Martinez-Carranza. 2017. “Real-Time Aerial Image Mosaicing Using Hashing-Based Matching.” 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), Sweden, IEEE, 144–149. doi:10.1109/RED-UAS.2017.8101658.
   Google Scholar
• DeTone, D., T. Malisiewicz, and A. Rabinovich. 2018. “SuperPoint: Self-Supervised Interest Point Detection and Description.” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Salt Lake City, UT, IEEE, 337–349. doi:10.1109/CVPRW.2018.00060.
   Google Scholar
• Dusmanu, M., I. Rocco, T. Pajdla, M. Pollefeys, J. Sivic, A. Torii, and T. Sattler. 2019. “D2-Net: A Trainable CNN for Joint Description and Detection of Local Features.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, IEEE, 8084–8093. doi:10.1109/CVPR.2019.00828.
   Google Scholar
• Grompone von Gioi, R., J. Jakubowicz, J. Morel, and G. Randall. 2010. “LSD: A Fast Line Segment Detector with a False Detection Control.” IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (4): 722–732. doi:10.1109/TPAMI.2008.300.
   PubMed Web of Science ®Google Scholar
• Han, X., T. Leung, Y. Jia, R. Sukthankar, and A. C. Berg. 2015. “MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching.” 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, IEEE, 3279–3286. doi:10.1109/CVPR.2015.7298948.
   Google Scholar
• Hartley, R. I. 1995. “In Defence of the 8-Point Algorithm.” IEEE International Conference on Computer Vision (ICCV), Cambridge, MA, USA, IEEE, 1064–1070. doi:10.1109/ICCV.1995.466816.
   Google Scholar
• He, M., Q. Guo, A. Li, J. Chen, B. Chen, and X. Feng. 2018. “Automatic Fast Feature-Level Image Registration for High-Resolution Remote Sensing Images.” Journal of Remote Sensing 22 (2): 277–292. doi:10.11834/jrs.20186420.
   Google Scholar
• He, J., S. Zhang, M. Yang, Y. Shan, and T. Huang. 2022. “BDCN: Bi-Directional Cascade Network for Perceptual Edge Detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence 44: 100–113. doi:10.1109/TPAMI.2020.3007074.
   PubMed Web of Science ®Google Scholar
• Huang, P.-H., K. Matzen, J. Kopf, N. Ahuja, and J.-B Huang. 2018a. “DeepMVS: Learning Multi-View Stereopsis.” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, USA, IEEE, 2821–2830. doi:10.1109/CVPR.2018.00298.
   Google Scholar
• Huang, K., Y. Wang, Z. Zhou, T. Ding, S. Gao, and Y. Ma. 2018b. “Learning to Parse Wireframes in Images of Man-Made Environments.” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, USA, IEEE, 626–635. doi:10.1109/CVPR.2018.00072.
   Google Scholar
• Kittler, J. 1983. “On the Accuracy of the Sobel Edge Detector.” Image and Vision Computing 1 (1): 37–42. doi:10.1016/0262-8856(83)90006-9
   Google Scholar
• Knapitsch, A., J. Park, Q. Y. Zhou, and V. Koltun. 2017. “Tanks and Temples: Benchmarking Large-Scale Scene Reconstruction.” ACM Transactions on Graphics 36 (4): 1. doi:10.1145/3072959.3073599
   Web of Science ®Google Scholar
• Lee, J. H., S. Lee, G. Zhang, J. Lim, W. K. Chung, and I. H. Suh. 2014. “Outdoor Place Recognition in Urban Environments Using Straight Lines.” 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, IEEE, 5550–5557. doi:10.1109/ICRA.2014.6907675.
   Google Scholar
• Leutenegger, S., M. Chli, and R. Y. Siegwart. 2011. “Brisk: Binary Robust Invariant Scalable Keypoints.” 2011 International Conference on Computer Vision (ICCV), Barcelona, Spain, IEEE, 2548–2555. doi:10.1109/ICCV.2011.6126542.
   Google Scholar
• Li, J., T. Yang, J. Yu, Z. Lu, P. Lu, X. Jia, and W. Chen. 2014. “Fast Aerial Video Stitching.” International Journal of Advanced Robotic Systems 11 (10): 167. doi:10.5772/59029.
   Google Scholar
• Li, H., H. Yu, J. Wang, W. Yang, L. Yu, and S. Scherer. 2021. “ULSD: Unified Line Segment Detection Across Pinhole, Fisheye, and Spherical Cameras.” ISPRS Journal of Photogrammetry and Remote Sensing 178: 187–202. doi:10.1016/j.isprsjprs.2021.06.004.
   Web of Science ®Google Scholar
• Lowe, D. G. 2004. “Distinctive Image Features from Scale-Invariant Keypoints.” International Journal of Computer Vision 60 (2): 91–110. doi:10.1023/B:VISI.0000029664.99615.94
   Web of Science ®Google Scholar
• Lu, X., J. Yao, K. Li, and L. Li. 2015. “CannyLines: A Parameter-Free Line Segment Detector.” 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada, IEEE, 507–511. doi:10.1109/ICIP.2015.7350850.
   Google Scholar
• Luo, Z., T. Shen, L. Zhou, J. Zhang, Y. Yao, S. Li, T. Fang, and L. Quan. 2019. “ContextDesc: Local Descriptor Augmentation With Cross-Modality Context.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, IEEE, 2522–2531. doi:10.1109/CVPR.2019.00263.
   Google Scholar
• Melekhov, I., A. Tiulpin, T. Sattler, M. Pollefeys, E. Rahtu, and J. Kannala. 2019. “DGC-Net: Dense Geometric Correspondence Network.” 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, USA, IEEE, 1034–1042. doi:10.1109/WACV.2019.00115.
   Google Scholar
• Mur-Artal, R., and J. D. Tardós. 2017. “ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras.” IEEE Transactions on Robotics 33 (5): 1255–1262. doi:10.1109/TRO.2017.2705103.
   Web of Science ®Google Scholar
• Newell, A., K. Yang, and J. Deng. 2016. “Stacked Hourglass Networks for Human Pose Estimation.” European Conference on Computer Vision (ECCV), Springer, 483–499. doi:10.1007/978-3-319-46484-8_29.
   Google Scholar
• Ono, Y., E. Trulls, P. Fua, and K. M. Yi. 2018. “LF-Net: Learning Local Features from Images.” 2018 Neural Information Processing Systems (NeurIPS), NY, USA, Curran Associates Inc., 6237–6247. doi:10.5555/3327345.3327521.
   Google Scholar
• Pautrat, R., J.-T. Lin, V. Larsson, M. R. Oswald, and M. Pollefeys. 2021. “SOLD2: Self-Supervised Occlusion-Aware Line Description and Detection.” 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, IEEE, 11363–11373. doi:10.1109/CVPR46437.2021.01121.
   Google Scholar
• Prewitt, J. M. S. 1970. “Object Enhancement and Extraction.” Picture Processing and Psychopictorics, 75–149.
   Google Scholar
• Pu, M., Y. Huang, Y. Liu, Q. Guan, and H. Ling. 2022. “EDTER: Edge Detection with Transformer.” 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, USA, IEEE, 1392–1402. doi:10.1109/CVPR52688.2022.00146.
   Google Scholar
• Revaud, J., P. Weinzaepfel, C. R. de Souza, N. Pion, G. Csurka, Y. Cabon, and M. Humenberger. 2019. “R2D2: Repeatable and Reliable Detector and Descriptor.” 2019 Neural Information Processing Systems (NeurIPS), Vancouver, British Columbia, Canada, Curran Associates Inc 12414–12424. doi:10.5555/3454287.3455400.
   Google Scholar
• Rublee, E., V. Rabaud, K. Konolige, and G. Bradski. 2011. “ORB an Efficient Alternative to SIFT or SURF.” 2011 International Conference on Computer Vision (ICCV), Barcelona, SPAIN, IEEE, 2564–2571. doi:10.1109/ICCV.2011.6126544.
   Google Scholar
• Sarlin, P.-E., D. DeTone, T. Malisiewicz, and A. Rabinovich. 2020. “SuperGlue: Learning Feature Matching With Graph Neural Networks.” 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, IEEE, 4937–4946. doi:10.1109/CVPR42600.2020.00499.
   Google Scholar
• Savinov, N., A. Seki, L. Ladický, T. Sattler, and M. Pollefeys. 2017. “Quad-Networks: Unsupervised Learning to Rank for Interest Point Detection.” 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, IEEE, 3929–3937. doi:10.1109/CVPR.2017.418.
   Google Scholar
• Schönberger, J. L., and J.-M. Frahm. 2016. “Structure-from-Motion Revisited.” 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, IEEE, 4104–4113. doi:10.1109/CVPR.2016.445.
   Google Scholar
• Schöps, T., J. L. Schönberger, S. Galliani, T. Sattler, K. Schindler, M. Pollefeys, and A. Geiger. 2017. “A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos.” 2017 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA, IEEE, 2538–2547. doi:10.1109/CVPR.2017.272.
   Google Scholar
• Shi, W., J. Caballero, F. Huszár, J. Totz, A. P. Aitken, R. Bishop, D. Rueckert, and Z. Wang. 2016. “Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network.” 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, IEEE, 1874–1883. doi:10.1109/CVPR.2016.207.
   Google Scholar
• Simo-Serra, E., E. Trulls, L. Ferraz, I. Kokkinos, P. Fua, and F. Moreno-Noguer. 2015. “Discriminative Learning of Deep Convolutional Feature Point Descriptors.” 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, IEEE, 118–126. doi:10.1109/ICCV.2015.22.
   Google Scholar
• Sinkhorn, R., and P. Knopp. 1967. “Concerning Nonnegative Matrices and Doubly Stochastic Matrices.” Pacific Journal of Mathematics 21 (2): 343–348. doi:10.2140/pjm.1967.21.343
   Web of Science ®Google Scholar
• Sun, J., Z. Shen, Y. Wang, H. Bao, and X. Zhou. 2021. “LoFTR: Detector-Free Local Feature Matching with Transformers.” 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, IEEE, 8918–8927. doi:10.1109/CVPR46437.2021.00881.
   Google Scholar
• Vaswani, A., N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin. 2017. “Attention is all you Need.” 2017 International Conference on Neural Information Processing Systems (NeurIPS). Red Hook, NY, USA, Curran Associates Inc., 6000–6010. doi:10.5555/3295222.3295349.
   Google Scholar
• Wang, G., Z. Zhai, B. Xu, and Y. Cheng. 2017. “A Parallel Method for Aerial Image Stitching Using orb Feature Points.” 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS), Wuhan, China, IEEE, 769–773. doi:10.1109/ICIS.2017.7960096.
   Google Scholar
• Wei, X., Y. Zhang, Z. Li, Y. Fu, and X. Xue. 2020. “DeepSFM: Structure from Motion via Deep Bundle Adjustment.” 2020 European Conference on Computer Vision (ECCV), Glasgow, UK, Springer, 230–247. doi:10.1007/978-3-030-58452-8_14.
   Google Scholar
• Xue, N., S. Bai, F. Wang, G. Xia, T. Wu, and L. Zhang. 2019. “Learning Attraction Field Representation for Robust Line Segment Detection.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, IEEE, 1595–1603. doi:10.1109/CVPR.2019.00169.
   Google Scholar
• Xue, N., T. Wu, S. Bai, F. Wang, G. S. Xia, L. Zhang, and P. H. S. Torr. 2020. “Holistically-Attracted Wireframe Parsing.” 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, IEEE, 2785–2794. doi:10.1109/CVPR42600.2020.00286.
   Google Scholar
• Yi, K. M., E. Trulls, V. Lepetit, and P. Fua. 2016. “Lecture Notes in Computer Science.” 2016 European Conference on Computer Vision (ECCV), Springer, 467–483. doi:10.1007/978-3-319-46466-4_28.
   Google Scholar
• Yu, Z., C. Feng, M.-Y. Liu, and S. Ramalingam. 2017. “CASENet: Deep Category-Aware Semantic Edge Detection.” 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, IEEE, 1761–1770. doi:10.1109/CVPR.2017.191.
   Google Scholar
• Zhang, Z. 1998. “Determining the Epipolar Geometry and its Uncertainty: A Review.” International Journal of Computer Vision 27 (2): 161–195. doi:10.1023/A:1007941100561
   Web of Science ®Google Scholar
• Zhou, Y., H. Qi, and Y. Ma. 2019. “End-to-End Wireframe Parsing.” 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, Korea (South), IEEE, 962–971. doi:10.1109/ICCV.2019.00105
   Google Scholar