Skip to search form
Skip to main content
Skip to account menu
Semantic Scholar
Semantic Scholar's Logo
Search 237,988,341 papers from all fields of science
Search
Sign In
Create Free Account
Scale-invariant feature transform
Known as:
Autopano-sift
, Scale invariant feature transform
, Autopano Pro
Expand
Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was…
Expand
Wikipedia
(opens in a new tab)
Create Alert
Alert
Related topics
Related topics
49 relations
3D modeling
AIBO
Augmented reality
Bag-of-words model in computer vision
Expand
Broader (1)
Feature detection (computer vision)
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm
Daliyah S. Aljutaili
,
Redna A. Almutlaq
,
Suha A. Alharbi
,
Dina M. Ibrahim
2018
Corpus ID: 51734427
Abstract— All currencies around the world look very different from each other. For instance, the size, color, and pattern of…
Expand
2016
2016
PENCOCOKAN OBYEK WAJAH MENGGUNAKAN METODE SIFT (SCALE INVARIANT FEATURE TRANSFORM)
Meidya Koeshardianto
2016
Corpus ID: 217623704
Pengenalan obyek merupakan penelitian yang menggabungkan konsep citra digital, pengenalan pola, matematika, dan statistik…
Expand
2012
2012
Improving Content Based Image Retrieval using Scale Invariant Feature Transform
M. Kamath
,
Disha Punjabi
,
Tejal Sabnis
,
Divya Upadhyay
,
Seema C. Shrawne
2012
Corpus ID: 63501993
Content-Based Image Retrieval (CBIR) is a challenging task. Common approaches use only low-level features. Notwithstanding, such…
Expand
2011
2011
Gradient-based musical feature extraction based on scale-invariant feature transform
T. Matsui
,
Masataka Goto
,
Jean-Philippe Vert
,
Yuji Uchiyama
European Signal Processing Conference
2011
Corpus ID: 10106290
We investigate a novel gradient-based musical feature extracted using a scale-invariant feature transform. This feature enables…
Expand
2010
2010
Is the “ Scale Invariant Feature Transform ” ( SIFT ) really Scale Invariant ?
J. Morel
,
Guoshen Yu
2010
Corpus ID: 145034898
This note is devoted to a mathematical exploration of whether Lowe’s Scale-Invariant Feature Transform (SIFT) [21], a very…
Expand
2009
2009
Performance Evaluation of Scale Invariant Feature Transform
Ajay Mittal
,
Navdeep Kaur
2009
Corpus ID: 122716730
The SIFT algorithm produces keypoint descriptors. This paper analyzes that the SIFT algorithm generates the number of keypoints…
Expand
2008
2008
Application of Scale Invariant Feature Transform to Image Matching
Renxiang Wang
2008
Corpus ID: 124419758
In order to improve the stability and reliability of image matching,application of the scale invariant feature transform(SIFT…
Expand
2007
2007
Scale Invariant Feature Transform for n-Dimensional Images (n-SIFT)
Warren Cheung
,
G. Hamarneh
The insight journal
2007
Corpus ID: 14996683
This document describes the implementation of several features previously developed[2], extending the 2D scale invariant feature…
Expand
2007
2007
IMAGE MATCHING USING SCALE INVARIANT FEATURE TRANSFORM ( SIFT )
Naotoshi Seo
,
D. Schug
2007
Corpus ID: 28027541
This paper explores the effectiveness of the Scale Invariant Feature Transform (SIFT) for image matching. There is a popularly…
Expand
2006
2006
Scale Invariant Feature Transform ( SIFT ) : Performance and Application
V. Andersen
,
Lars Pellarin
,
R. A. June
2006
Corpus ID: 16595587
In 2004, David G. Lowe published his paper “Distinctive Image Features from ScaleInvariant Keypoints” (Lowe, 2004, [2…
Expand