338
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Remote sensing image feature matching via graph classification with local motion consistency

, &
Article: 2308713 | Received 07 Sep 2023, Accepted 17 Jan 2024, Published online: 06 Feb 2024

References

  • Barath, Daniel, Jiri Matas, and Jana Noskova. 2019. “MAGSAC: Marginalizing Sample Consensus.” Paper presented at the Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.
  • Barfoot, Timothy D. 2017. State Estimation for Robotics. Cambridge: Cambridge University Press.
  • Bay, Herbert, Tinne Tuytelaars, and Luc Van Gool. 2006. “Surf: Speeded up Robust Features.” Paper presented at the Computer Vision–ECCV 2006: 9th European Conference on Computer Vision, Graz, Austria, May 7–13, 2006. Proceedings, Part I 9.
  • Bian, JiaWang, Wen-Yan Lin, Yasuyuki Matsushita, Sai-Kit Yeung, Tan-Dat Nguyen, and Ming-Ming Cheng. 2017. “Gms: Grid-Based Motion Statistics for Fast, Ultra-Robust Feature Correspondence.” Paper presented at the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
  • Bian, Jia-Wang, Yu-Huan Wu, Ji Zhao, Yun Liu, Le Zhang, Ming-Ming Cheng, and Ian Reid. 2019. “An Evaluation of Feature Matchers for Fundamental Matrix Estimation.” arXiv preprint arXiv:1908.09474.
  • Calonder, Michael, Vincent Lepetit, Christoph Strecha, and Pascal Fua. 2010. “Brief: Binary Robust Independent Elementary Features.” Paper presented at the Computer Vision–ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5–11, 2010, Proceedings, Part IV 11.
  • Delmerico, Jeffrey, Titus Cieslewski, Henri Rebecq, Matthias Faessler, and Davide Scaramuzza. 2019. “Are we Ready for Autonomous Drone Racing? The UZH-FPV Drone Racing Dataset.” Paper presented at the 2019 International Conference on Robotics and Automation (ICRA).
  • Engel, J., V. Koltun, and D. Cremers. 2018. “Direct Sparse Odometry.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (3): 611–625. https://doi.org/10.1109/TPAMI.2017.2658577.
  • Forster, Christian, Matia Pizzoli, and Davide Scaramuzza. 2014. “SVO: Fast Semi-Direct Monocular Visual Odometry.” Paper presented at the 2014 IEEE International Conference on Robotics and Automation (ICRA).
  • Gao, Hongyang, and Shuiwang Ji. 2019. “Graph u-Nets.” Paper presented at the International Conference on Machine Learning.
  • Ham, Hanry, Julian Wesley, and Hendra Hendra. 2019. “Computer Vision Based 3D Reconstruction: A Review.” International Journal of Electrical and Computer Engineering 9 (4): 2394.
  • Hamilton, Will, Zhitao Ying, and Jure Leskovec. 2017. “Inductive Representation Learning on Large Graphs.” Advances in Neural Information Processing Systems 30: 1025–1035.
  • Harel, Jonathan, Christof Koch, and Pietro Perona. 2006. “Graph-based Visual Saliency.” Advances in Neural Information Processing Systems 19: 545–552.
  • Horn, Berthold KP, and Brian G Schunck. 1981. “Determining Optical Flow.” Artificial Intelligence 17 (1-3): 185–203. https://doi.org/10.1016/0004-3702(81)90024-2.
  • Itoh, Takeshi D, Takatomi Kubo, and Kazushi Ikeda. 2022. “Multi-level Attention Pooling for Graph Neural Networks: Unifying Graph Representations with Multiple Localities.” Neural Networks 145: 356–373. https://doi.org/10.1016/j.neunet.2021.11.001.
  • Jiang, Xingyu, Junjun Jiang, Aoxiang Fan, Zhongyuan Wang, and Jiayi Ma. 2019. “Multiscale Locality and Rank Preservation for Robust Feature Matching of Remote Sensing Images.” IEEE Transactions on Geoscience and Remote Sensing 57 (9): 6462–6472. https://doi.org/10.1109/tgrs.2019.2906183.
  • Jiang, Xingyu, Jiayi Ma, Guobao Xiao, Zhenfeng Shao, and Xiaojie Guo. 2021. “A Review of Multimodal Image Matching: Methods and Applications.” Information Fusion 73: 22–71. https://doi.org/10.1016/j.inffus.2021.02.012.
  • Jiang, Xingyu, Yifan Xia, Xiao-Ping Zhang, and Jiayi Ma. 2022. “Robust Image Matching via Local Graph Structure Consensus.” Pattern Recognition 126. https://doi.org/10.1016/j.patcog.2022.108588.
  • Jiayi, Ma, Zhao Ji, Tian Jinwen, A. L. Yuille, and Tu Zhuowen. 2014. “Robust Point Matching via Vector Field Consensus.” IEEE Transactions on Image Processing 23 (4): 1706–1721. https://doi.org/10.1109/TIP.2014.2307478.
  • Kadir, Timor, Andrew Zisserman, and Michael Brady. 2004. “An Affine Invariant Salient Region Detector.” Paper presented at the Computer Vision-ECCV 2004: 8th European Conference on Computer Vision, Prague, Czech Republic, May 11–14, 2004. Proceedings, Part I 8.
  • Kingma, Diederik P, and Jimmy Ba. 2014. “Adam: A Method for Stochastic Optimization.” arXiv preprint arXiv:1412.6980.
  • Leutenegger, Stefan, Margarita Chli, and Roland Y Siegwart. 2011. “BRISK: Binary Robust Invariant Scalable Keypoints.” Paper presented at the 2011 International Conference on Computer Vision.
  • Li, Xiangru, and Zhanyi Hu. 2010. “Rejecting Mismatches by Correspondence Function.” International Journal of Computer Vision 89: 1–17. https://doi.org/10.1007/s11263-010-0318-x.
  • Lin, Hui, Peijun Du, Weichang Zhao, Lianpeng Zhang, and Huasheng Sun. 2010. “Image Registration Based on Corner Detection and Affine Transformation.” Paper presented at the 2010 3rd International Congress on Image and Signal Processing.
  • Lin, Wen-Yan, Fan Wang, Ming-Ming Cheng, Sai-Kit Yeung, Philip HS Torr, Minh N Do, and Jiangbo Lu. 2017. “CODE: Coherence Based Decision Boundaries for Feature Correspondence.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (1): 34–47.
  • Lowe, David G. 2004. “Distinctive Image Features from Scale-Invariant Keypoints.” International Journal of Computer Vision 60: 91–110. https://doi.org/10.1023/B:VISI.0000029664.99615.94.
  • Ma, Jiayi, Aoxiang Fan, Xingyu Jiang, and Guobao Xiao. 2022. “Feature Matching via Motion-Consistency Driven Probabilistic Graphical Model.” International Journal of Computer Vision 130 (9): 2249–2264. https://doi.org/10.1007/s11263-022-01644-2.
  • Ma, Jiayi, Ji Zhao, Junjun Jiang, Huabing Zhou, and Xiaojie Guo. 2019. “Locality Preserving Matching.” International Journal of Computer Vision 127: 512–531. https://doi.org/10.1007/s11263-018-1117-z.
  • Ma, Ailong, Yanfei Zhong, and Liangpei Zhang. 2015. “Adaptive Multiobjective Memetic Fuzzy Clustering Algorithm for Remote Sensing Imagery.” IEEE Transactions on Geoscience and Remote Sensing 53 (8): 4202–4217. https://doi.org/10.1109/TGRS.2015.2393357.
  • Mikolajczyk, Krystian, and Cordelia Schmid. 2004. “Scale & Affine Invariant Interest Point Detectors.” International Journal of Computer Vision 60: 63–86. https://doi.org/10.1023/B:VISI.0000027790.02288.f2.
  • Nie, Lang, Chunyu Lin, Kang Liao, Shuaicheng Liu, and Yao Zhao. 2021. “Unsupervised Deep Image Stitching: Reconstructing Stitched Features to Images.” IEEE Transactions on Image Processing 30: 6184–6197. https://doi.org/10.1109/TIP.2021.3092828.
  • Rublee, Ethan, Vincent Rabaud, Kurt Konolige, and Gary Bradski. 2011. “ORB: An Efficient Alternative to SIFT or SURF.” Paper presented at the 2011 International Conference on Computer Vision.
  • Sarlin, Paul-Edouard, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich. 2020. “Superglue: Learning Feature Matching with Graph Neural Networks.” Paper presented at the Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.
  • Tola, Engin, Vincent Lepetit, and Pascal Fua. 2009. “Daisy: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo.” IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (5): 815–830. https://doi.org/10.1109/TPAMI.2009.77.
  • Torr, Philip HS, and Andrew Zisserman. 2000. “MLESAC: A new Robust Estimator with Application to Estimating Image Geometry.” Computer Vision and Image Understanding 78 (1): 138–156. https://doi.org/10.1006/cviu.1999.0832.
  • Triggs, Bill, Philip F McLauchlan, Richard I Hartley, and Andrew W Fitzgibbon. 2000. “Bundle Adjustment—A Modern Synthesis.” Paper presented at the Vision Algorithms: Theory and Practice: International Workshop on Vision Algorithms Corfu, Greece, September 21–22, 1999 Proceedings.
  • Velickovic, Petar, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. “Graph Attention Networks.” stat 1050 (20): 10-48550.
  • Vinyals, Oriol, Samy Bengio, and Manjunath Kudlur. 2015. “Order Matters: Sequence to Sequence for Sets.” arXiv preprint arXiv:1511.06391.
  • Wang, Xintao, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy. 2018. “Esrgan: Enhanced Super-Resolution Generative Adversarial Networks.” Paper presented at the Proceedings of the European Conference on Computer Vision (ECCV) Workshops.
  • Wong, Hoi Sim, Tat-Jun Chin, Jin Yu, and David Suter. 2011. “Dynamic and Hierarchical Multi-Structure Geometric Model Fitting.” Paper presented at the 2011 International Conference on Computer Vision.
  • Wu, Chen, Liangpei Zhang, and Bo Du. 2017. “Kernel Slow Feature Analysis for Scene Change Detection.” IEEE Transactions on Geoscience and Remote Sensing 55 (4): 2367–2384. https://doi.org/10.1109/TGRS.2016.2642125.
  • Xia, Y., and J. Ma. 2022. “Locality-Guided Global-Preserving Optimization for Robust Feature Matching.” IEEE Transactions on Image Processing 31: 5093–5108. https://doi.org/10.1109/TIP.2022.3192993.
  • Xu, Keyulu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2018. “How Powerful are Graph Neural Networks?” arXiv preprint arXiv:1810.00826.
  • Yi, Kwang Moo, Eduard Trulls, Yuki Ono, Vincent Lepetit, Mathieu Salzmann, and Pascal Fua. 2018. “Learning to Find Good Correspondences.” Paper presented at the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
  • Zhang, Jiahui, Dawei Sun, Zixin Luo, Anbang Yao, Lei Zhou, Tianwei Shen, Yurong Chen, Long Quan, and Hongen Liao. 2019. “Learning two-View Correspondences and Geometry Using Order-Aware Network.” Paper presented at the Proceedings of the IEEE/CVF International Conference on Computer Vision.
  • Zhang, S., H. Tong, J. Xu, and R. Maciejewski. 2019. “Graph Convolutional Networks: A Comprehensive Review.” Comput Soc Netw 6 (1): 11. https://doi.org/10.1186/s40649-019-0069-y.