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PDF Distinctive Image Features from Scale-Invariant Keypoints

The Scale-Invariant Feature Transform (or SIFT) algorithm is a highly robust method to extract and con-sequently match distinctive invariant features from Lowe describes a way to eciently extract a great amount of robust features from an image that are ro-tation and scale invariant and are robust to...

https://pdfs.semanticscholar.org/268c/d46a06e8e3052bbd64e96fac73d600430281.pdf

PDF Compare and Reweight: Distinctive Image

Distinctive Image Captioning Using Similar Images Sets. In the image caption dataset, the image I0 is provided with N annotated ground-truth captions C0 = {c01, c02, . . . , c0N }. We rst nd K similar images {I1, I2, . . . , IK } that are semantically similar to I0, and then calculate the CIDErBtw values of...

https://arxiv.org/pdf/2007.06877.pdf

[aMMAI_02] Distinctive Image Features from Scale-Invariant Keypoints

The SIFT feature is widely used in image feature representation, either directly or after quantized (as in " visual words "). Another global feature, HOG (Histogram of Oriented Gradients), also borrows the ideas of the keypoint descriptor in SIFT. While the SIFT feature is robust, it has patent issues and is...

https://ryanlei.wordpress.com/2011/03/09/ammai_02-distinctive-image-features-from-scale-invariant-keypoints/

[Paper Summary Lec_02] Distinctive Image Features from...

" Distinctive Image Features from Scale-Invariant Keypoints, ". Lowe IJCV 2004. The feature presented in this paper is well known as SIFT, which is widely used in matching task between objects in computer vision community.

http://r00944004ammai.blogspot.com/2012/03/paper-summary-lec02-distinctive-image.html

Distinctive Image Features from Scale-Invariant Keypoints

Key requirements for good feature    Highly distinctive, with a low probability of mismatch Should be easy to extract Invariance: - Scale and rotation - change in illumination - slight change in viewing angle - image noise - clutter and occlusion Brief History  Moravec(1981)

https://studylib.net/doc/14972912/distinctive-image-features-from-scale-invariant-keypoints

[Reading] Lecture 03 - Distinctive Image Features from...

SIFT is such a powerful method to extract distinctive feature points that can be used not only in CBIR, but also in object recognition, image matching, stereo vision, and so on. Since different cameras can capture the same scene in different positions, in different times, with different viewing angles...

http://ugtony.blogspot.com/2008/02/reading-week-2-distinctive-image.html

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Distinctive Image Features from Scale-Invariant Keypoints | BibSonomy

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...

https://www.bibsonomy.org/bibtex/2c9984d3a783a48553018a518847f6657/daill

Compare and Reweight: Distinctive Image Captioning Using Similar...

Image captioning, a popular topic in computer vision, has achieved substantial progress in recent years. However, the distinctiveness of natural descriptions is often overlooked in previous work. It is closely related to the quality of captions, as distinctive captions are more likely to describe images with their...

https://www.researchgate.net/publication/342944539_Compare_and_Reweight_Distinctive_Image_Captioning_Using_Similar_Images_Sets