Distance-based descriptors and their application in the task of object detection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86093010" target="_blank" >RIV/61989100:27240/14:86093010 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-11752-2_40" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-11752-2_40</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-11752-2_40" target="_blank" >10.1007/978-3-319-11752-2_40</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Distance-based descriptors and their application in the task of object detection

Popis výsledku v původním jazyce

In this paper, we propose an efficient and interesting way how to encode the shape of the objects. A lot of state-of-the art descriptors (e.g. HOG, Haar, LBP) are based on the fact that the shape of the objects can be described by brightness differencesinside the image. It means that the descriptors encode the gradient or intensity differences inside the image (i.e. edges). In the cases that the edges are very thin, the edge information can be difficult to obtain and the dimensionally of feature vector(without the method for reduction) is typically large and contains redundant information. These ills are motivation for the proposed method in that the edges need not be hit directly; the input brightness function is transformed using the appropriate image distance function. After this transformation, the values of distance function inside objects and backgrounds are different and the values can be used for description of object appearance. We demonstrate the properties of the method fo

Název v anglickém jazyce

Distance-based descriptors and their application in the task of object detection

Popis výsledku anglicky

In this paper, we propose an efficient and interesting way how to encode the shape of the objects. A lot of state-of-the art descriptors (e.g. HOG, Haar, LBP) are based on the fact that the shape of the objects can be described by brightness differencesinside the image. It means that the descriptors encode the gradient or intensity differences inside the image (i.e. edges). In the cases that the edges are very thin, the edge information can be difficult to obtain and the dimensionally of feature vector(without the method for reduction) is typically large and contains redundant information. These ills are motivation for the proposed method in that the edges need not be hit directly; the input brightness function is transformed using the appropriate image distance function. After this transformation, the values of distance function inside objects and backgrounds are different and the values can be used for description of object appearance. We demonstrate the properties of the method fo

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Computer Science. Volume 8753

ISBN

978-3-319-11751-5

ISSN

0302-9743

e-ISSN

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Počet stran výsledku

11

Strana od-do

488-498

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Münster

Datum konání akce

2. 9. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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