AWEAR 2.0 System: Omni-directional Audio-Visual Data Acquisition and Processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00163104" target="_blank" >RIV/68407700:21230/09:00163104 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/CVPRW.2009.5204361" target="_blank" >http://dx.doi.org/10.1109/CVPRW.2009.5204361</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CVPRW.2009.5204361" target="_blank" >10.1109/CVPRW.2009.5204361</a>

Jazyk výsledku

angličtina

Název v původním jazyce

AWEAR 2.0 System: Omni-directional Audio-Visual Data Acquisition and Processing

Popis výsledku v původním jazyce

We present a wearable audio-visual capturing system, termed AWEAR 2.0, along with its underlying vision components that allow robust self-localization, multi-body pedestrian tracking, and dense scene reconstruction. Designed as a backpack, the system isaimed at supporting the cognitive abilities of the wearer. In this paper, we focus on the design issues for the hardware platform and on the performance of the current state-of-the-art computer vision methods on the acquired sequences. We describe the calibration procedure of the two omni-directional cameras present in the system as well as a Structure-from-Motion pipeline that allows for stable multi-body tracking even from rather shaky video sequences thanks to ground plane stabilization. Furthermore,we show how a dense scene reconstruction can be obtained from the data acquired with the platform.

Název v anglickém jazyce

AWEAR 2.0 System: Omni-directional Audio-Visual Data Acquisition and Processing

Popis výsledku anglicky

We present a wearable audio-visual capturing system, termed AWEAR 2.0, along with its underlying vision components that allow robust self-localization, multi-body pedestrian tracking, and dense scene reconstruction. Designed as a backpack, the system isaimed at supporting the cognitive abilities of the wearer. In this paper, we focus on the design issues for the hardware platform and on the performance of the current state-of-the-art computer vision methods on the acquired sequences. We describe the calibration procedure of the two omni-directional cameras present in the system as well as a Structure-from-Motion pipeline that allows for stable multi-body tracking even from rather shaky video sequences thanks to ground plane stabilization. Furthermore,we show how a dense scene reconstruction can be obtained from the data acquired with the platform.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/GA201%2F07%2F1136" target="_blank" >GA201/07/1136: Matematika neurčitosti</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

EGOVIS 2009: Proceedings of the First Workshop on Egocentric Vision

ISBN

978-1-4244-3994-2

ISSN

1063-6919

e-ISSN

—

Počet stran výsledku

8

Strana od-do

49-56

Název nakladatele

Omnipress

Místo vydání

Madison

Místo konání akce

Miami

Datum konání akce

20. 6. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000274887100007