SURF: Speeded Up Robust Features. In this paper, we present a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features). It approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster. This is achieved by relying on integral images for image convolutions; by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor); and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard evaluation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF’s strong performance.

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  1. Arseev, S. P.; Mestetskiy, L. M.: Character skeleton as a pen trace model for recognition from reconstructed trace (2021)
  2. Casillas-Perez, David; Pizarro, Daniel; Fuentes-Jimenez, David; Mazo, Manuel; Bartoli, Adrien: The isowarp: the template-based visual geometry of isometric surfaces (2021)
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  4. Fursov, V. A.; Minaev, E. Yu.; Kotov, A. P.: Vehicle motion estimation using visual observations of the elevation surface (2021)
  5. Garcia-Salguero, Mercedes; Gonzalez-Jimenez, Javier: Fast and robust certifiable estimation of the relative pose between two calibrated cameras (2021)
  6. Garcia-Salguero, Mercedes; Gonzalez-Jimenez, Javier: A sufficient condition of optimality for the relative pose problem between cameras (2021)
  7. Ma, Jiayi; Jiang, Xingyu; Fan, Aoxiang; Jiang, Junjun; Yan, Junchi: Image matching from handcrafted to deep features: a survey (2021)
  8. Ren, Chaofeng; Zhi, Xiaodong; Pu, Yuchi; Zhang, Fuqiang: A multi-scale UAV image matching method applied to large-scale landslide reconstruction (2021)
  9. Xu, Tianyang; Feng, Zhenhua; Wu, Xiao-Jun; Kittler, Josef: Adaptive channel selection for robust visual object tracking with discriminative correlation filters (2021)
  10. Álvarez-Miranda, Eduardo; Díaz-Guerrero, John: Multicriteria saliency detection: a (exact) robust network design approach (2020)
  11. Bobkov, V. A.; Kudryashov, A. P.: Identification and recovery of trajectories of dynamic objects from stereo images (2020)
  12. Gao, Depeng; Wu, Rui; Liu, Jiafeng; Fan, Xiaopeng; Tang, Xianglong: Finding robust transfer features for unsupervised domain adaptation (2020)
  13. Kovač, Ivan; Marák, Pavol: Openfinger: towards a combination of discriminative power of fingerprints and finger vein patterns in multimodal biometric system (2020)
  14. Lindeberg, Tony: Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade (2020)
  15. Maanicshah, Kamal; Azam, Muhammad; Nguyen, Hieu; Bouguila, Nizar; Fan, Wentao: Finite inverted beta-Liouville mixture models with variational component splitting (2020)
  16. Olver, Peter J.; Qu, Changzheng; Yang, Yun: Feature matching and heat flow in centro-affine geometry (2020)
  17. Park, Soyoung; Carriquiry, Alicia: An algorithm to compare two-dimensional footwear outsole images using maximum cliques and speeded-up robust feature (2020)
  18. Sharma, Vipul; Mir, Roohie Naaz: A comprehensive and systematic look up into deep learning based object detection techniques: a review (2020)
  19. Vinay, A.; Singh, Ankur; Anand, Nikhil; Raj, Mayank; Bharati, Aniket; Murthy, K. N. B.; Natarajan, S.: Facial image classification using rotation, illumination, scale and expression invariant dense features and ENN (2020)
  20. Wu, Min; Wicker, Matthew; Ruan, Wenjie; Huang, Xiaowei; Kwiatkowska, Marta: A game-based approximate verification of deep neural networks with provable guarantees (2020)

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