SIFT

SIFT Keypoint Detector. Distinctive Image Features from Scale-Invariant Keypoints. This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The features are highly distinctive, in the sense that a single feature can be correctly matched with high probability against a large database of features from many images. This paper also describes an approach to using these features for object recognition. The recognition proceeds by matching individual features to a database of features from known objects using a fast nearest-neighbor algorithm, followed by a Hough transform to identify clusters belonging to a single object, and finally performing verification through least-squares solution for consistent pose parameters. This approach to recognition can robustly identify objects among clutter and occlusion while achieving near real-time performance.


References in zbMATH (referenced in 591 articles )

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  1. Meyers, Ethan; Wolf, Lior: Using biologically inspired features for face processing (2008) ioport
  2. Panin, Giorgio; Knoll, Alois: Mutual information-based 3D object tracking (2008) ioport
  3. Pilet, Julien; Lepetit, Vincent; Fua, Pascal: Fast non-rigid surface detection, registration and realistic augmentation (2008) ioport
  4. Rav-Acha, Alex; Engel, Giora; Peleg, Shmuel: Minimal aspect distortion (MAD) mosaicing of long scenes (2008) ioport
  5. Shen, Min-yi; Xiang, Zhi-yu; Liu, Ji-lin: Vision based terrain reconstruction for planet rover using a special binocular bundle adjustment (2008)
  6. Shen, Ye-Hu; Liu, Ji-Lin; Du, Xin: Environment map building and localization for robot navigation based on image sequences (2008)
  7. Siddiqi, Kaleem; Zhang, Juan; Macrini, Diego; Shokoufandeh, Ali; Bouix, Sylvain; Dickinson, Sven: Retrieving articulated 3-D models using medial surfaces (2008)
  8. Sinzinger, Eric D.: A model-based approach to junction detection using radial energy (2008)
  9. Snavely, Noah; Seitz, Steven M.; Szeliski, Richard: Modeling the world from internet photo collections (2008) ioport
  10. Spyrou, Evaggelos; Tolias, Giorgos; Mylonas, Phivos; Avrithis, Yannis: Concept detection and keyframe extraction using a visual thesaurus (2008) ioport
  11. Stamos, Ioannis; Liu, Lingyun; Chen, Chao; Wolberg, George; Yu, Gene; Zokai, Siavash: Integrating automated range registration with multiview geometry for the photorealistic modeling of large-scale scenes (2008) ioport
  12. Sudderth, Erik B.; Torralba, Antonio; Freeman, William T.; Willsky, Alan S.: Describing visual scenes using transformed objects and parts (2008) ioport
  13. Trinh, Hoang-Hon; Kim, Dae-Nyeon; Jo, Kang-Hyun: Facet-based multiple building analysis for robot intelligence (2008)
  14. Volegov, D. B.; Yurin, D. V.: Preliminary coarse image registration by using straight lines found on them for constructing super resolution mosaics and 3D scene recovery (2008)
  15. Wang, Yizhou; Zhu, Song-Chun: Perceptual scale-space and its applications (2008) ioport
  16. Wu, Er-Yong; Li, Gong-Yan; Xiang, Zhi-Yu; Liu, Ji-Lin: Stereo vision based SLAM using Rao-Blackwellised particle filter (2008)
  17. Zheng, Yan-Tao; Neo, Shi-Yong; Chua, Tat-Seng; Tian, Qi: Toward a higher-level visual representation for object-based image retrieval (2008) ioport
  18. Boiman, Oren; Irani, Michal: Detecting irregularities in images and in video (2007) ioport
  19. Brown, Matthew; Lowe, David G.: Automatic panoramic image stitching using invariant features (2007) ioport
  20. Cao, Frédéric; Delon, Julie; Desolneux, Agnès; Musé, Pablo; Sur, Frédéric: A unified framework for detecting groups and application to shape recognition (2007) ioport

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