Dynamic movement primitives for human movement recognition

Name: Dynamic movement primitives for human movement recognition
Author: Pehlivan, Alp Burak, Öztop, Erhan

İsim	Dynamic movement primitives for human movement recognition
Yazar	Pehlivan, Alp Burak, Öztop, Erhan
Basım Tarihi:	2015
Basım Yeri	- IEEE
Konu	DMP, HMM, Recognition, Human movement, Kinect, Comparison
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-147991762-4
Kayıt Numarası	d2e0d150-da98-4ed5-9d05-c9342b58ba5a
Lokasyon	Computer Science
Tarih	2015
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	Dynamic Movement Primitives (DMPs)-originally a method for movement trajectory generation [1] has been also used for recognition tasks [2, 3]. However there has not been a systematic comparison between other recognition methods and DMPs using human movement data. This paper presents a comparison of commonly used Hidden Markov Model (HMM) based recognition with DMP based recognition using human generated letter trajectories. As the working principles of these two methods are very different, in addition to the performance, the numbers of adaptable parameters that are used in each method and, process time were compared. The results, indicate that HMM gives better results than DMP, with possible noise robustness advantage in DMPs for human movement.
DOI	10.1109/IECON.2015.7392424

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Özyeğin Üniversitesi

Kaynağa git

Dynamic movement primitives for human movement recognition

Yazar Pehlivan, Alp Burak, Öztop, Erhan

Basım Tarihi 2015

Basım Yeri - IEEE

Konu DMP, HMM, Recognition, Human movement, Kinect, Comparison

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-147991762-4

Kayıt Numarası d2e0d150-da98-4ed5-9d05-c9342b58ba5a

Lokasyon Computer Science

Tarih 2015

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin Dynamic Movement Primitives (DMPs)-originally a method for movement trajectory generation [1] has been also used for recognition tasks [2, 3]. However there has not been a systematic comparison between other recognition methods and DMPs using human movement data. This paper presents a comparison of commonly used Hidden Markov Model (HMM) based recognition with DMP based recognition using human generated letter trajectories. As the working principles of these two methods are very different, in addition to the performance, the numbers of adaptable parameters that are used in each method and, process time were compared. The results, indicate that HMM gives better results than DMP, with possible noise robustness advantage in DMPs for human movement.

DOI 10.1109/IECON.2015.7392424