Szczegóły publikacji

Opis bibliograficzny

Effectiveness comparison of Kinect and Kinect 2 for recognition of Oyama karate techniques / Tomasz Hachaj, Marek R. OGIELA, Katarzyna KOPTYRA // W: NBiS 2015 [Dokument elektroniczny] : 18th international conference on Network-Based Information Systems : 2–4 September 2015, Taipei, Taiwan / ed. by Leonard Barolli, [et al.]. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2015. — 1 dysk optyczny. — ISBN: 978-1-4799-9942-2; e-ISBN: 978-1-4799-9941-5. — S. 332–337. — Wymagania systemowe: Adobe Reader ; napęd CD-ROM. — Bibliogr. s. 336–337, Abstr.

Autorzy (3)

Słowa kluczowe

Gesture Description LanguageOyama karateKinectaction recognitionclassification

Dane bibliometryczne

ID BaDAP95058
Data dodania do BaDAP2016-01-08
DOI10.1109/NBiS.2015.51
Rok publikacji2015
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
KonferencjaInternational Conference on Network-Based Information Systems 2015

Abstract

The aim of this research is to evaluate effectiveness of Kinect and Kinect 2 for recognition of specialized actions namely Oyama karate techniques. As a classification algorithm we have used Gesture Description Language (GDL) classifier. We have recorded a dataset that contains motion (MoCap) recordings of two professional sport (black belt) instructors and masters of Oyama Karate. The whole dataset contained 200 movement samples per person (400 samples per Kinect camera, so totally we had 800 samples). After data was captured it was split into two subsets: training and validation. Each subset contained only recordings of a single user. We have performed 2 fold cross validation switching the role of user data between training and validation set. In all cases but two MoCap data from Kinect 2 appeared to be more reliable than from Kinect 1 taking into account both recognition rates of GDL classifier and error classification cases. Also in case of Kinect 1 standard deviation of results were higher which means that classifier becomes less stable while trained on data from older device. The ability of more accurate calculation of legs joints positions seems to be biggest advantages of Kinect 2 over its predecessor.

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#76801Data dodania: 22.10.2013
Dependence of Kinect sensors number and position on gestures recognition with Gesture Description Language semantic classifier / Tomasz Hachaj, Marek R. OGIELA, Marcin Piekarczyk // W: FedCSIS : abstracts of the Federated Conference on Computer Science and Information Systems : September 8–11, 2013, Kraków, Poland. — [Piscataway : IEEE], [2013]. — Opis częśc. wg okł. — ISBN: 978-1-4673-4471-5. — S. 55. — Pełny tekst na dołączonym Dysku Flash. — S. 575–579. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 579, Abstr. — Toż w bazie IEEE Xplore. — S. 571–575. — Tryb dostępu http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6644058. — Bibliogr. s. 575, Abstr. — W bazie Web of Science wersja drukowana: 2013 Federated Conference on Computer Science and Information Systems (FEDCSIS). — ISBN 978-1-4673-4471-5. — S. 571–575. — W bazie WoS Brak afiliacji AGH
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#95084Data dodania: 7.1.2016
Application of Hidden Markov Models and Gesture Description Language classifiers to Oyama karate techniques recognition / Tomasz Hachaj, Marek R. OGIELA, Katarzyna KOPTYRA // W: IMIS-2015 [Dokument elektroniczny] : ninth international conference on Innovative Mobile and Internet Services in ubiquitous computing : 8–10 July 2015, Blumenau, Brazil : proceedings / ed. by Leonard Barolli, [et al.]. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2015. — ISBN: 978-1-4799-8873-0. — S. 160–165. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: http://ieeexplore.ieee.org.ieee-xplore.wbg2.bg.agh.edu.pl/sta... [2016-01-05]. — Bibliogr. s. 164–165, Abstr.