Presentation	2007-09-04 Gradient-Based Feature Extraction : SIFT and HOG Hironobu Fujiyoshi,
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Abstract(in English)	Scale-Invariant Feature. Transform(SIFT) is an approach for detecting and extracting local feature descriptors that are reasonably invariant to changes in illumination, image noise, rotation, scaling, and small changes in viewpoint. Because the SIFT algorithm can describe characteristics of feature points that are invariant to scale and rotation changes, it has been used for image matching such as image mosaicing and generic object recognition. In this paper, we describe the SIFT algorithm and introduce applications that use it. We also describe another, algorithm called "Histograms of Oriented Gradients(HOG)" which is based on gradient feature extraction similar to,the SIFT algorithm. We also introduce an example of how HOG can be used for people detection.
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Paper #	PRMU2007-82,HIP2007-91
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Committee	PRMU
Conference Date	2007/8/27(1days)
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Registration To	Pattern Recognition and Media Understanding (PRMU)
Language	JPN
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Title (in English)	Gradient-Based Feature Extraction : SIFT and HOG
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1st Author's Name	Hironobu Fujiyoshi
1st Author's Affiliation	Dept. of Computer Science, Chubu University()
Date	2007-09-04
Paper #	PRMU2007-82,HIP2007-91
Volume (vol)	vol.107
Number (no)	206
Page	pp.pp.-
#Pages	14
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