Author
Pehlivan, Alp Burak, Öztop, Erhan
Publication Date
2015
Publication Place
-
IEEE
Subject
DMP, HMM, Recognition, Human movement, Kinect, Comparison
Type
Document
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
978-147991762-4
Record ID
d2e0d150-da98-4ed5-9d05-c9342b58ba5a
Library Location
Computer Science
Date
2015
Notes
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text
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
