About: Motion-Based Tracking of Multiple Low-Relative-Depth Objects

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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	In this report, we present a method for online tracking of multiple rigid low-relative-depth objects or object surfaces from a single moving or static camera. The method determines the number of tracked entities in the scene automatically and initialises them without any human interaction or by running a specific object detector. Tracking is formulated as an energy-based multi-model fitting problem based on displacement of a semi-dense set of local Lukas-Kanade trackers. An over-complete set of motion models is generated in each frame and fitted considering the motion similarity. For each detected surface the motion model is propagated in time and to ensure temporal consistency and locality of the tracked entities in the scene two novel energy terms are introduced. We demonstrate the abilities of the proposed algorithm on several long real-world sequences. The algorithm works at 2-6fps depending on the complexity of the scene. In this report, we present a method for online tracking of multiple rigid low-relative-depth objects or object surfaces from a single moving or static camera. The method determines the number of tracked entities in the scene automatically and initialises them without any human interaction or by running a specific object detector. Tracking is formulated as an energy-based multi-model fitting problem based on displacement of a semi-dense set of local Lukas-Kanade trackers. An over-complete set of motion models is generated in each frame and fitted considering the motion similarity. For each detected surface the motion model is propagated in time and to ensure temporal consistency and locality of the tracked entities in the scene two novel energy terms are introduced. We demonstrate the abilities of the proposed algorithm on several long real-world sequences. The algorithm works at 2-6fps depending on the complexity of the scene. (en)
Title	Motion-Based Tracking of Multiple Low-Relative-Depth Objects Motion-Based Tracking of Multiple Low-Relative-Depth Objects (en)
skos:prefLabel	Motion-Based Tracking of Multiple Low-Relative-Depth Objects Motion-Based Tracking of Multiple Low-Relative-Depth Objects (en)
skos:notation	RIV/68407700:21230/12:00200616!RIV13-GA0-21230___
http://linked.open...avai/predkladatel	Fakulta elektrotechnická
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GBP103/12/G084)
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Matas, Jiří Šochman, Jan
http://linked.open.../riv/druhVysledku	O - Ostatní výsledky nezařaditelné do žádného z výše uvedených druhů výsledku
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	151904
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/12:00200616
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	tracking; motion segmentation; on-line (en)
http://linked.open.../riv/klicoveSlovo	tracking on-line motion segmentation
http://linked.open...ontrolniKodProRIV	[42F88FC06325]
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	Center for Large Scale Multi-modal Data Interpretation
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Matas, Jiří Šochman, Jan
http://localhost/t...ganizacniJednotka	21230

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