About: Inter-stage Feature Propagation in Cascade Building with AdaBoost

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Není k dispozici (cs) A modification of the cascaded detector with the AdaBoost trained stage classifiers is proposed and brought to bear on the face detection problem. The cascaded detector is a sequential classifier with the ability of early rejection of easy samples. Each decision in the sequence is made by a separately trained classifier, a stage classifier. In proposed modification the features from one stage of training are propagated to the next stage classifier. The proposed intra-stage feature propagation is shown to be greedily optimal, does not increase computational complexity of the stage classifier and leads to shorter stage classifiers and accordingly to faster detectors. A cascaded face detector is built with the intra-stage feature propagation and is compared with the Viola and Jones approach. The same detection and false positive rates are achieved with a detector that is 25 perc. faster and consists of only two thirds of the weak classifiers needed for a cascade trained by the Viola and J A modification of the cascaded detector with the AdaBoost trained stage classifiers is proposed and brought to bear on the face detection problem. The cascaded detector is a sequential classifier with the ability of early rejection of easy samples. Each decision in the sequence is made by a separately trained classifier, a stage classifier. In proposed modification the features from one stage of training are propagated to the next stage classifier. The proposed intra-stage feature propagation is shown to be greedily optimal, does not increase computational complexity of the stage classifier and leads to shorter stage classifiers and accordingly to faster detectors. A cascaded face detector is built with the intra-stage feature propagation and is compared with the Viola and Jones approach. The same detection and false positive rates are achieved with a detector that is 25 perc. faster and consists of only two thirds of the weak classifiers needed for a cascade trained by the Viola and J (en)
Title	Není k dispozici (cs) Inter-stage Feature Propagation in Cascade Building with AdaBoost Inter-stage Feature Propagation in Cascade Building with AdaBoost (en)
skos:prefLabel	Není k dispozici (cs) Inter-stage Feature Propagation in Cascade Building with AdaBoost Inter-stage Feature Propagation in Cascade Building with AdaBoost (en)
skos:notation	RIV/68407700:21230/04:03103428!RIV/2005/GA0/212305/N
http://linked.open.../vavai/riv/strany	236 ; 239
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA102/02/1539)
http://linked.open...vai/riv/dodaniDat	2005
http://linked.open...aciTvurceVysledku	Matas, Jiří Šochman, Jan
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
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	568759
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/04:03103428
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	AdaBoost; computer vision; face detection (en)
http://linked.open.../riv/klicoveSlovo	AdaBoost computer vision face detection
http://linked.open...ontrolniKodProRIV	[17045DC8E090]
http://linked.open...v/mistoKonaniAkce	Cambridge
http://linked.open...i/riv/mistoVydani	Los Alamitos
http://linked.open...i/riv/nazevZdroje	Proceedings of ICPR 2004 17th International Conference on Pattern Recognition
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Recognition of faces (in unconstrained environments) from a single example image
http://linked.open...UplatneniVysledku	2004
http://linked.open...iv/tvurceVysledku	Matas, Jiří Šochman, Jan
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2004-08-23 (xsd:date)
number of pages	4 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE Computer Society Press
https://schema.org/isbn	0-7695-2128-2
http://localhost/t...ganizacniJednotka	21230

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