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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F14%3A86093009%21RIV15-MSM-27240___
rdf:type
skos:Concept n13:Vysledek
rdfs:seeAlso
http://www.scopus.com/inward/record.url?eid=2-s2.0-84906919935&partnerID=40&md5=93e1e77974e3cee269bbc3d3fd4d6c15
dcterms:description
In this paper, we propose a novel technique for object description. The proposed method is based on investigation of energy distribution (in the image) that describes the properties of objects. The energy distribution is encoded into a vector of features and the vector is then used as an input for the SVM classifier. Generally, the technique can be used for detecting arbitrary objects. In this paper, however, we demonstrate the robustness of the proposed descriptors for solving the problem of car detection. Compared with the state-of-the-art descriptors (e.g. HOG, Haar-like features), the proposed approach achieved better results, especially from the viewpoint of dimensionality of the feature vector; the proposed approach is able to successfully describe the objects of interest with a relatively small set of numbers without the use of methods for the reduction of feature vector In this paper, we propose a novel technique for object description. The proposed method is based on investigation of energy distribution (in the image) that describes the properties of objects. The energy distribution is encoded into a vector of features and the vector is then used as an input for the SVM classifier. Generally, the technique can be used for detecting arbitrary objects. In this paper, however, we demonstrate the robustness of the proposed descriptors for solving the problem of car detection. Compared with the state-of-the-art descriptors (e.g. HOG, Haar-like features), the proposed approach achieved better results, especially from the viewpoint of dimensionality of the feature vector; the proposed approach is able to successfully describe the objects of interest with a relatively small set of numbers without the use of methods for the reduction of feature vector
dcterms:title
Energy based descriptors and their application for car detection Energy based descriptors and their application for car detection
skos:prefLabel
Energy based descriptors and their application for car detection Energy based descriptors and their application for car detection
skos:notation
RIV/61989100:27240/14:86093009!RIV15-MSM-27240___
n3:aktivita
n17:S
n3:aktivity
S
n3:dodaniDat
n11:2015
n3:domaciTvurceVysledku
n14:3014622 n14:5185297 n14:9112995 n14:4899423
n3:druhVysledku
n9:D
n3:duvernostUdaju
n21:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
14584
n3:idVysledku
RIV/61989100:27240/14:86093009
n3:jazykVysledku
n12:eng
n3:klicovaSlova
recognition; object detection; image features
n3:klicoveSlovo
n20:object%20detection n20:recognition n20:image%20features
n3:kontrolniKodProRIV
[FDF40A976280]
n3:mistoKonaniAkce
Lisabon
n3:mistoVydani
[Portugalsko]
n3:nazevZdroje
VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
n3:obor
n22:IN
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:rokUplatneniVysledku
n11:2014
n3:tvurceVysledku
Mozdřeň, Karel Sojka, Eduard Šurkala, Milan Fusek, Radovan
n3:typAkce
n4:WRD
n3:zahajeniAkce
2014-01-05+01:00
s:numberOfPages
8
n5:doi
10.5220/0004685804920499
n6:hasPublisher
SciTePress - Science and Technology Publications
n15:isbn
978-989-758-003-1
n16:organizacniJednotka
27240