Scale-invariant feature transform

Known as: Autopano-sift, Scale invariant feature transform, Autopano Pro 
Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was… (More)
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Topic mentions per year

2003-2017
05020032017

Papers overview

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2014
2014
Face recognition includes analysis of an image and extracting its facial features which will help to discriminate it from others… (More)
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2013
2013
Scale-invariant feature transform (SIFT) was an algorithm in computer vision to detect and describe local features in images. Due… (More)
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2012
2012
Object recognition is an important task in the computer vision field as it has many applications, including optical character… (More)
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Highly Cited
2011
Highly Cited
2011
The Scale-Invariant Feature Transform (or SIFT) algorithm is a highly robust method to extract and consequently match distinctive… (More)
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2010
2010
The resolutions offered by today's multimedia vary significantly owing to the development of video technology. For example, there… (More)
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2009
2009
This paper presents a novel approach to digital video stabilization that uses adaptive particle filter for global motion… (More)
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2009
2009
In shot boundary detection, the key technology is to compute the visual content discontinuity values between consecutive video… (More)
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2007
2007
To monitor road situation, the source from CCTV is more useful than any other data from GPS or loop detector because it can give… (More)
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2006
2006
In this paper, we present a self-calibration strategy to estimate camera intrinsic and extrinsic parameters using the scale… (More)
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2006
2006
Scene understanding is an important problem in intelligent robotics. Since visual information is uncertain due to several reasons… (More)
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