Kinect-Supported Dataset Creation for Human Pose Estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F14%3APU112026" target="_blank" >RIV/00216305:26230/14:PU112026 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1145/2643188.2643195" target="_blank" >http://dx.doi.org/10.1145/2643188.2643195</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/2643188.2643195" target="_blank" >10.1145/2643188.2643195</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Kinect-Supported Dataset Creation for Human Pose Estimation

Popis výsledku v původním jazyce

Dataset creation of annotated human poses is very time-consuming. This paper presents an approach for rapid construction of a precisely annotated training dataset for human pose estimation of a sitting subject, intended especially for aeronautic cockpit. We propose to use Kinect as a tool for collecting ground truth to a purely visual dataset (for reasons defined by the application, use of Kinect or similar structured light-based approaches is impossible).  Since Kinect annotation of individual joints might be imprecise at certain moments, manual post-processing of the acquired data is necessary and we propose a scheme for efficient and reliable manual post-annotation. We produced a dataset of 6,322 annotated frames, involving 11 human subjects recorded in various light condition, different clothing, and varying background. Each frame contains one seated person in frontal view with annotation of pose and optical flow data.

Název v anglickém jazyce

Kinect-Supported Dataset Creation for Human Pose Estimation

Popis výsledku anglicky

Dataset creation of annotated human poses is very time-consuming. This paper presents an approach for rapid construction of a precisely annotated training dataset for human pose estimation of a sitting subject, intended especially for aeronautic cockpit. We propose to use Kinect as a tool for collecting ground truth to a purely visual dataset (for reasons defined by the application, use of Kinect or similar structured light-based approaches is impossible).  Since Kinect annotation of individual joints might be imprecise at certain moments, manual post-processing of the acquired data is necessary and we propose a scheme for efficient and reliable manual post-annotation. We produced a dataset of 6,322 annotated frames, involving 11 human subjects recorded in various light condition, different clothing, and varying background. Each frame contains one seated person in frontal view with annotation of pose and optical flow data.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20206 - Computer hardware and architecture

Projekt

<a href="/cs/project/7E13047" target="_blank" >7E13047: Applying Pilots Models for Safer Aircraft - A-PiMod</a><br>

Návaznosti

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

Proceedings of Spring Conference on Computer Graphics

ISBN

978-80-223-3601-7

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

88-95

Název nakladatele

Comenius University in Bratislava

Místo vydání

Smolenice

Místo konání akce

Smolenice

Datum konání akce

27. 5. 2014

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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