About: Learning Efficient Linear Predictors for Motion Estimation

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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	A novel object representation for tracking is proposed. The tracked object is represented as a constellation of spatially localised linear predictors which are learned on a single training image. In the learning stage, sets of pixels whose intensities allow for optimal least square predictions of the transformations are selected as a support of the linear predictor. The approach comprises three contributions: learning object specific linear predictors, explicitly dealing with the predictor precision - computational complexity trade-off and selecting a view-specific set of predictors suitable for global object motion estimate. Robustness to occlusion is achieved by RANSAC procedure. The learned tracker is very efficient, achieving frame rate generally higher than 30 frames per second despite the Matlab implementation. A novel object representation for tracking is proposed. The tracked object is represented as a constellation of spatially localised linear predictors which are learned on a single training image. In the learning stage, sets of pixels whose intensities allow for optimal least square predictions of the transformations are selected as a support of the linear predictor. The approach comprises three contributions: learning object specific linear predictors, explicitly dealing with the predictor precision - computational complexity trade-off and selecting a view-specific set of predictors suitable for global object motion estimate. Robustness to occlusion is achieved by RANSAC procedure. The learned tracker is very efficient, achieving frame rate generally higher than 30 frames per second despite the Matlab implementation. (en)
Title	Learning Efficient Linear Predictors for Motion Estimation Learning Efficient Linear Predictors for Motion Estimation (en)
skos:prefLabel	Learning Efficient Linear Predictors for Motion Estimation Learning Efficient Linear Predictors for Motion Estimation (en)
skos:notation	RIV/68407700:21230/06:00124649!RIV11-GA0-21230___
http://linked.open...avai/riv/aktivita	P R S V
http://linked.open...avai/riv/aktivity	P(1ET101210407), P(GA201/06/1821), R, S, V
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Matas, Jiří Zimmermann, Karel Svoboda, Tomáš
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	483046
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/06:00124649
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	motion estimation; real-time; tracking (en)
http://linked.open.../riv/klicoveSlovo	tracking real-time motion estimation
http://linked.open...ontrolniKodProRIV	[662BB12951DC]
http://linked.open...v/mistoKonaniAkce	Madurai
http://linked.open...i/riv/mistoVydani	Berlin
http://linked.open...i/riv/nazevZdroje	Proceedings of 5th Indian Conference on Computer Vision, Graphics and Image Processing
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...vavai/riv/projekt	Multi-camera system for modeling and recognition of events Algorithms of image recognition
http://linked.open...UplatneniVysledku	2006
http://linked.open...iv/tvurceVysledku	Matas, Jiří Svoboda, Tomáš Zimmermann, Karel Hilton, A.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open...ain/vavai/riv/wos	000244671700040
http://linked.open.../riv/zahajeniAkce	2006-12-13 (xsd:date)
issn	0302-9743
number of pages	12 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-540-68301-8
http://localhost/t...ganizacniJednotka	21230

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