About: Sub-linear Indexing for Large Scale Object Recognition

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Sub-linear Indexing for Large Scale Object Recognition Goto Sponge Distinct Permalink

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

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Není k dispozici (cs) Realistic approaches to large scale object recognition, i.e. for detection and localisation of hundreds or more objects, must support sub-linear time indexing. In the paper, we propose a method capable of recognising one of N objects in log(N) time. The .visual memory. is organised as a binary decision tree that is built to minimise average time to decision. Leaves of the tree represent a few local image areas, and each non-terminal node is associated with a .weak classifier.. In the recognition phase, a single invariant measurement decides in which subtree a corresponding image area is sought. The method preserves all the strengths of local affine region methods . robustness to background clutter, occlusion, and large changes of viewpoints. Experimentally we show that it supports near real-time recognition of hundreds of objects with state-of-the-art recognition rates. After the test image is processed (in a second on a current PCs), the recognition via indexing into the visual memory Realistic approaches to large scale object recognition, i.e. for detection and localisation of hundreds or more objects, must support sub-linear time indexing. In the paper, we propose a method capable of recognising one of N objects in log(N) time. The .visual memory. is organised as a binary decision tree that is built to minimise average time to decision. Leaves of the tree represent a few local image areas, and each non-terminal node is associated with a .weak classifier.. In the recognition phase, a single invariant measurement decides in which subtree a corresponding image area is sought. The method preserves all the strengths of local affine region methods . robustness to background clutter, occlusion, and large changes of viewpoints. Experimentally we show that it supports near real-time recognition of hundreds of objects with state-of-the-art recognition rates. After the test image is processed (in a second on a current PCs), the recognition via indexing into the visual memory (en)
Title	Sub-linear Indexing for Large Scale Object Recognition Není k dispozici (cs) Sub-linear Indexing for Large Scale Object Recognition (en)
skos:prefLabel	Sub-linear Indexing for Large Scale Object Recognition Není k dispozici (cs) Sub-linear Indexing for Large Scale Object Recognition (en)
skos:notation	RIV/68407700:21230/05:03114548!RIV06-GA0-21230___
http://linked.open.../vavai/riv/strany	1 ; 10
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA102/03/0440)
http://linked.open...vai/riv/dodaniDat	2006
http://linked.open...aciTvurceVysledku	Matas, Jiří Obdržálek, Štěpán
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	545351
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/05:03114548
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	LAF; MSER; Object recognition; local affine frames (en)
http://linked.open.../riv/klicoveSlovo	MSER LAF Object recognition local affine frames
http://linked.open...ontrolniKodProRIV	[3BCB9CF2FD85]
http://linked.open...v/mistoKonaniAkce	Oxford
http://linked.open...i/riv/mistoVydani	London
http://linked.open...i/riv/nazevZdroje	BMVC 2005: Proceedings of the 16th British Machine Vision Conference
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	Recognizing human activities for automated video surveillance
http://linked.open...UplatneniVysledku	2005
http://linked.open...iv/tvurceVysledku	Matas, Jiří Obdržálek, Štěpán
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2005-09-05 (xsd:date)
number of pages	10 (xsd:int)
http://purl.org/ne...btex#hasPublisher	British Machine Vision Association
https://schema.org/isbn	1-901725-29-4
http://localhost/t...ganizacniJednotka	21230
is http://linked.open...avai/riv/vysledek of	Sub-linear Indexing for Large Scale Object Recognition

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software