Rotation-Invariant Image and Video Description With Local Binary Pattern Features

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00192658" target="_blank" >RIV/68407700:21230/12:00192658 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/TIP.2011.2175739" target="_blank" >http://dx.doi.org/10.1109/TIP.2011.2175739</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TIP.2011.2175739" target="_blank" >10.1109/TIP.2011.2175739</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Rotation-Invariant Image and Video Description With Local Binary Pattern Features

Popis výsledku v původním jazyce

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, wepresent LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its re

Název v anglickém jazyce

Rotation-Invariant Image and Video Description With Local Binary Pattern Features

Popis výsledku anglicky

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, wepresent LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its re

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/GAP103%2F10%2F1585" target="_blank" >GAP103/10/1585: Pokročilé prediktory pro detekci a sledování objektů ve videu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

IEEE Transactions on Image Processing

ISSN

1057-7149

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

1465-1477

Kód UT WoS článku

000302181800004

EID výsledku v databázi Scopus

—