About: Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images

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

About: Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images Goto Sponge NotDistinct 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	This paper addresses object detection and tracking in high-resolution omnidirectional images. The foreseen application is a visual subsystem of a rescue robot equipped with an omnidirectional camera, which demands real time efficiency and robustness against changing viewpoint. Object detectors typically do not guarantee specific frame rate. The detection time may vastly depend on a scene complexity and image resolution. The adapted tracker can often help to overcome the situation, where the appearance of the object is far from the training set. On the other hand, once a tracker is lost, it almost never finds the object again. We propose a combined solution where a very efficient tracker (based on sequential linear predictors) incrementally accommodates varying appearance and speeds up the whole process. We experimentally show that the performance of the combined algorithm, measured by a ratio between false positives and false negatives, outperforms both individual algorithms. This paper addresses object detection and tracking in high-resolution omnidirectional images. The foreseen application is a visual subsystem of a rescue robot equipped with an omnidirectional camera, which demands real time efficiency and robustness against changing viewpoint. Object detectors typically do not guarantee specific frame rate. The detection time may vastly depend on a scene complexity and image resolution. The adapted tracker can often help to overcome the situation, where the appearance of the object is far from the training set. On the other hand, once a tracker is lost, it almost never finds the object again. We propose a combined solution where a very efficient tracker (based on sequential linear predictors) incrementally accommodates varying appearance and speeds up the whole process. We experimentally show that the performance of the combined algorithm, measured by a ratio between false positives and false negatives, outperforms both individual algorithms. (en)
Title	Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images (en)
skos:prefLabel	Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images (en)
skos:notation	RIV/68407700:21230/11:00187102!RIV12-MSM-21230___
http://linked.open...avai/predkladatel	Fakulta elektrotechnická
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(7E10044), P(GAP103/10/1585), P(GPP103/11/P700)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Zimmermann, Karel Svoboda, Tomáš Hurych, David
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	199366
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/11:00187102
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	detection; tracking; incremental; learning; predictors; fern; omnidirectional; high-resolution (en)
http://linked.open.../riv/klicoveSlovo	tracking high-resolution incremental omnidirectional detection learning predictors fern
http://linked.open...ontrolniKodProRIV	[34360B28917D]
http://linked.open...v/mistoKonaniAkce	Algarve
http://linked.open...i/riv/mistoVydani	Setúbal
http://linked.open...i/riv/nazevZdroje	Proceedings of VISAPP 2011 International Conference on Computer Vision Theory and Applications
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Advanced predictors for object detection and tracking in video Application of regression methods for tracking of unknown objects Natural human-robot cooperation in dynamic environments
http://linked.open...UplatneniVysledku	2011
http://linked.open...iv/tvurceVysledku	Svoboda, Tomáš Zimmermann, Karel Hurych, David
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-03-05 (xsd:date)
number of pages	10 (xsd:int)
http://purl.org/ne...btex#hasPublisher	INSTICC Press
https://schema.org/isbn	978-989-8425-47-8
http://localhost/t...ganizacniJednotka	21230
is http://linked.open...avai/riv/vysledek of	Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images Fast Learnable Object Tracking and Detection in High-resolution Omnidirectional Images

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, 38 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software