About: Energy-transfer features and their application in the task of face detection

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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)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6636631
Description	In this paper, we describe a novel and interesting approach for extracting the image features. The features we propose are efficient and robust; the feature vectors of relatively small dimensions are sufficient for successful recognition. We call them the energy-transfer features. In contrast, the classical features (e.g. HOG, Haar features) that are combined with the trainable classifiers (e.g. a support vector machine, neural network) require large training sets due to their high dimensionality. The large training sets are difficult to acquire in many cases. In addition to that, the large training sets slow down the training phase. Moreover, the high dimension of feature vector also slows down the detection phase and the methods for the reduction of feature vector must be used. These shortcomings became the motivation for creating the features that are able to describe the object of interest with a relatively small number of numerical values without the use of methods for the reduction of feature vector. In this paper, we demonstrate the properties of our features in the task of face detection. In this paper, we describe a novel and interesting approach for extracting the image features. The features we propose are efficient and robust; the feature vectors of relatively small dimensions are sufficient for successful recognition. We call them the energy-transfer features. In contrast, the classical features (e.g. HOG, Haar features) that are combined with the trainable classifiers (e.g. a support vector machine, neural network) require large training sets due to their high dimensionality. The large training sets are difficult to acquire in many cases. In addition to that, the large training sets slow down the training phase. Moreover, the high dimension of feature vector also slows down the detection phase and the methods for the reduction of feature vector must be used. These shortcomings became the motivation for creating the features that are able to describe the object of interest with a relatively small number of numerical values without the use of methods for the reduction of feature vector. In this paper, we demonstrate the properties of our features in the task of face detection. (en)
Title	Energy-transfer features and their application in the task of face detection Energy-transfer features and their application in the task of face detection (en)
skos:prefLabel	Energy-transfer features and their application in the task of face detection Energy-transfer features and their application in the task of face detection (en)
skos:notation	RIV/61989100:27240/13:86088599!RIV14-MSM-27240___
http://linked.open...avai/riv/aktivita	S
http://linked.open...avai/riv/aktivity	S
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Mozdřeň, Karel Sojka, Eduard Šurkala, Milan Fusek, Radovan
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	Vysoká škola báňská - Technická univerzita Ostrava / Fakulta elektrotechniky a informatiky
http://linked.open...dnocenehoVysledku	72895
http://linked.open...ai/riv/idVysledku	RIV/61989100:27240/13:86088599
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Training phase; Numerical values; Image features; High dimensions; High dimensionality; Haar features; Feature vectors; Detection phase (en)
http://linked.open.../riv/klicoveSlovo	Feature vectors Haar features High dimensionality Numerical values Training phase Detection phase High dimensions Image features
http://linked.open...ontrolniKodProRIV	[806431702071]
http://linked.open...v/mistoKonaniAkce	Krakow
http://linked.open...i/riv/mistoVydani	Piscataway
http://linked.open...i/riv/nazevZdroje	2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Fusek, Radovan Mozdřeň, Karel Sojka, Eduard Šurkala, Milan
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2013-08-27 (xsd:date)
number of pages	6 (xsd:int)
http://bibframe.org/vocab/doi	10.1109/AVSS.2013.6636631
http://purl.org/ne...btex#hasPublisher	IEEE
https://schema.org/isbn	978-1-4799-0703-8
http://localhost/t...ganizacniJednotka	27240

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