About: Robust Scale-Adaptive Mean-Shift for Tracking

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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	Mean-Shift tracking is a popular algorithm for object tracking since it is easy to implement and it is fast and robust. In this paper, we address the problem of scale adaptation of the Hellinger distance based Mean-Shift tracker. We start from a theoretical derivation of scale estimation in the Mean-Shift framework. To make the scale estimation robust and suitable for tracking, we in- troduce regularization terms that counter two major problem: (i) scale expansion caused by background clutter and (ii) scale implosion on self-similar objects. To further robustify the scale estimate, it is validated by a forward-backward consis- tency check. The proposed Mean-shift tracker with scale selection is compared with re- cent state-of-the-art algorithms on a dataset of 48 public color sequences and it achieved excellent results. Mean-Shift tracking is a popular algorithm for object tracking since it is easy to implement and it is fast and robust. In this paper, we address the problem of scale adaptation of the Hellinger distance based Mean-Shift tracker. We start from a theoretical derivation of scale estimation in the Mean-Shift framework. To make the scale estimation robust and suitable for tracking, we in- troduce regularization terms that counter two major problem: (i) scale expansion caused by background clutter and (ii) scale implosion on self-similar objects. To further robustify the scale estimate, it is validated by a forward-backward consis- tency check. The proposed Mean-shift tracker with scale selection is compared with re- cent state-of-the-art algorithms on a dataset of 48 public color sequences and it achieved excellent results. (en)
Title	Robust Scale-Adaptive Mean-Shift for Tracking Robust Scale-Adaptive Mean-Shift for Tracking (en)
skos:prefLabel	Robust Scale-Adaptive Mean-Shift for Tracking Robust Scale-Adaptive Mean-Shift for Tracking (en)
skos:notation	RIV/68407700:21230/13:00212540!RIV14-TA0-21230___
http://linked.open...avai/predkladatel	Fakulta elektrotechnická
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GBP103/12/G084), P(TE01020415)
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Matas, Jiří Vojíř, 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	103173
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/13:00212540
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	object tracking; mean-shift; scale estimation (en)
http://linked.open.../riv/klicoveSlovo	object tracking scale estimation mean-shift
http://linked.open...ontrolniKodProRIV	[DB127715649A]
http://linked.open...v/mistoKonaniAkce	Espoo
http://linked.open...i/riv/mistoVydani	Heidelberg
http://linked.open...i/riv/nazevZdroje	SCIA 2013: Proceedings of the 18th Scandinavian Conference on Image Analysis
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Center for Large Scale Multi-modal Data Interpretation V3C - Visual Computing Competence Center
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Matas, Jiří Nosková, Jana Vojíř, Tomáš
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2013-06-17 (xsd:date)
issn	0302-9743
number of pages	12 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-642-38886-6_61
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-642-38885-9
http://localhost/t...ganizacniJednotka	21230

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