Continuous Action Recognition Based on Sequence Alignment

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00230191" target="_blank" >RIV/68407700:21230/15:00230191 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s11263-014-0758-9" target="_blank" >http://dx.doi.org/10.1007/s11263-014-0758-9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11263-014-0758-9" target="_blank" >10.1007/s11263-014-0758-9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Continuous Action Recognition Based on Sequence Alignment

Popis výsledku v původním jazyce

Continuous action recognition is more challenging than isolated recognition beca use classification and segmentation must be simultaneously carried out. We build on the well k nown dynamic time warping framework and devise a novel visual alignment technique, namely dyna mic frame warping (DFW), which performs isolated recognition based on per-frame representation of videos, and on aligning a test sequence with a model sequence. Moreover, we propose two ex tensions which enable to perform recognition concomitant with segmentation, namely one-pass DF W and two-pass DFW. These two methods have their roots in the domain of continuous recognition of speech and, to the best of our knowledge, their extension to continuous visual action reco gnition has been overlooked. We test and illustrate the proposed techniques with a recently re leased dataset (RAVEL) and with two public-domain datasets widely used in action recognition ( Hollywood-1 and Hollywood-2).We also compare the performances of t

Název v anglickém jazyce

Continuous Action Recognition Based on Sequence Alignment

Popis výsledku anglicky

Continuous action recognition is more challenging than isolated recognition beca use classification and segmentation must be simultaneously carried out. We build on the well k nown dynamic time warping framework and devise a novel visual alignment technique, namely dyna mic frame warping (DFW), which performs isolated recognition based on per-frame representation of videos, and on aligning a test sequence with a model sequence. Moreover, we propose two ex tensions which enable to perform recognition concomitant with segmentation, namely one-pass DF W and two-pass DFW. These two methods have their roots in the domain of continuous recognition of speech and, to the best of our knowledge, their extension to continuous visual action reco gnition has been overlooked. We test and illustrate the proposed techniques with a recently re leased dataset (RAVEL) and with two public-domain datasets widely used in action recognition ( Hollywood-1 and Hollywood-2).We also compare the performances of t

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

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

International Journal of Computer Vision

ISSN

0920-5691

e-ISSN

—

Svazek periodika

112

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

25

Strana od-do

90-114

Kód UT WoS článku

000350361500005

EID výsledku v databázi Scopus

2-s2.0-84925543513