About: Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://doi.ieeecomputersociety.org/10.1109/TPAMI.2010.89
Description	In this paper, we present Linear Discriminant Projections (LDP) for reducing dimensionality and improving discriminability of local image descriptors. We place LDP into the context of state-of-the-art discriminant projections and analyze its properties. LDP requires a large set of training data with point-to-point correspondence ground truth. We demonstrate that training data produced by a simulation of image transformations leads to nearly the same results as the real data with correspondence ground truth. This makes it possible to apply LDP as well as other discriminant projection approaches to the problems where the correspondence ground truth is not available, such as image categorization. We perform an extensive experimental evaluation on standard data sets in the context of image matching and categorization. We demonstrate that LDP enables significant dimensionality reduction of local descriptors and performance increases in different applications. The results improve upon the st In this paper, we present Linear Discriminant Projections (LDP) for reducing dimensionality and improving discriminability of local image descriptors. We place LDP into the context of state-of-the-art discriminant projections and analyze its properties. LDP requires a large set of training data with point-to-point correspondence ground truth. We demonstrate that training data produced by a simulation of image transformations leads to nearly the same results as the real data with correspondence ground truth. This makes it possible to apply LDP as well as other discriminant projection approaches to the problems where the correspondence ground truth is not available, such as image categorization. We perform an extensive experimental evaluation on standard data sets in the context of image matching and categorization. We demonstrate that LDP enables significant dimensionality reduction of local descriptors and performance increases in different applications. The results improve upon the st (en)
Title	Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors (en)
skos:prefLabel	Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors (en)
skos:notation	RIV/68407700:21230/11:00175557!RIV12-MSM-21230___
http://linked.open...avai/riv/aktivita	Z
http://linked.open...avai/riv/aktivity	Z(MSM6840770038)
http://linked.open...iv/cisloPeriodika	2
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Matas, Jiří
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	209130
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/11:00175557
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Linear discriminant projections; dimensionality reduction; image descriptors; image recognition; image matching (en)
http://linked.open.../riv/klicoveSlovo	Linear discriminant projections image descriptors image matching dimensionality reduction image recognition
http://linked.open...odStatuVydavatele	US - Spojené státy americké
http://linked.open...ontrolniKodProRIV	[FB1827899949]
http://linked.open...i/riv/nazevZdroje	IEEE Transactions on Pattern Analysis and Machine Intelligence
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...UplatneniVysledku	2011
http://linked.open...v/svazekPeriodika	33
http://linked.open...iv/tvurceVysledku	Matas, Jiří Cai, Hongping Mikolajczyk, K.
http://linked.open...ain/vavai/riv/wos	000285313200010
http://linked.open...n/vavai/riv/zamer	Decision Making and Control for Manufacturing III
issn	0162-8828
number of pages	15 (xsd:int)
http://bibframe.org/vocab/doi	10.1109/TPAMI.2010.89
http://localhost/t...ganizacniJednotka	21230

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