Distinctive Image Features from Scale-Invariant Keypoints
Citations
570 citations
Cites methods from "Distinctive Image Features from Sca..."
...The approach used in the matching of SIFT key features allows preliminary matches that are invariant to large changes in scale and rotation to be made [39]....
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...The first stage of the SfM algorithm is then used to identify projections of the same features in space from two or more views using the Scale Invariant Feature Transform (SIFT) technique developed in [39]....
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562 citations
Cites background or methods from "Distinctive Image Features from Sca..."
..., fðIÞ corresponds to extracting SIFT descriptors [20], followed by pooling into a bag-of-words vector [21] or a VLAD vector [24]), here we propose to learn the representation fðIÞ in an end-to-end manner, directly optimized for the task of place recognition....
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...Recently, after publication of the first version of thiswork [79], [77] and [78] achieved even better results on the image retrieval tasks by using stronger supervision in the form of automatically cleaned-up image correspondences obtained with structure-from-motion, i.e., precise matching of RootSIFT descriptors and spatial verification....
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...local feature based compact descriptor, which consists of VLAD pooling [24] with intra-normalization [23] on top of densely extracted RootSIFTs [20], [48]....
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...7 compares the top ranked images of our method versus the best baseline (RootSIFT+ VLAD+whitening); additional examples are shown in the appendix, available online....
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...5 also shows that our trained fVLAD representation with whitening based on VGG16 ( ) convincingly outperforms RootSIFT +VLAD+whitening, as well as the method of Torii et al. [10], and therefore sets the state-of-the-art for compact descriptors on all benchmarks....
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561 citations
Cites methods from "Distinctive Image Features from Sca..."
...In object detection and recognition, descriptors like HOG [9] and SIFT [17] use histograms of gradients....
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559 citations
553 citations
Cites background or methods from "Distinctive Image Features from Sca..."
...The algorithm for extracting HOGs (see Dalal and Triggs, 2005; Lowe, 2004) counts occurrences of edge orientations in a local neighborhood of an image....
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...HOGs are extracted from a regular grid of non-overlapped patches covering the whole normalized image....
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...1 shows an example patch with their corresponding HOGs....
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...Recently, Histograms of Oriented Gradients (HOGs) have proven to be an effective descriptor for object recognition in general and face recognition in particular....
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...Histograms of Oriented Gradients (HOGs) (Lowe, 2004) are image descriptors invariant to 2D rotation which have been used in many different problems in computer vision, such as pedestrian detection (Bertozzi et al., 2007; Wang and Lien, 2007; Chuang et al., 2008; Watanabe et al., 2009; Baranda et al., 2008; He et al., 2008; Kobayashi et al., 2008; Suard et al., 2006; Zhu et al., 2006; ll rights reserved....
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