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Action Recognition Online with Hierarchical Self-Organizing Maps

Gharaee, Zahra LU ; Gärdenfors, Peter LU and Johnsson, Magnus LU (2016) 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems p.538-544
Abstract
We present a hierarchical self-organizing map based system for online recognition of human actions. We have made a first evaluation of our system by training it on two different sets of recorded human actions, one set containing manner actions and one set containing result actions, and then tested it by letting a human performer carry out the actions online in real time in front of the system’s 3D-camera. The system successfully recognized more than 94% of the manner actions and most of the result actions carried out by the human performer.
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
12th International Conference on Signal Image Technology & Internet-Based Systems : SITIS 2016. Proceedings. - SITIS 2016. Proceedings.
pages
7 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2016 12th International Conference on Signal-Image Technology & Internet-Based Systems
conference location
Naples, Italy
conference dates
2016-11-28 - 2016-12-01
external identifiers
  • scopus:85019192205
  • wos:000406473000081
ISBN
978-1-5090-5698-9
DOI
10.1109/SITIS.2016.91
project
Ikaros: An infrastructure for system level modelling of the brain
Thinking in Time: Cognition, Communication and Learning
language
English
LU publication?
yes
id
d77dcd94-e940-4ff0-8488-d5f03e5ba049
alternative location
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7907518
date added to LUP
2016-12-04 17:12:46
date last changed
2025-04-04 15:05:39
@inproceedings{d77dcd94-e940-4ff0-8488-d5f03e5ba049,
  abstract     = {{We present a hierarchical self-organizing map based system for online recognition of human actions. We have made a first evaluation of our system by training it on two different sets of recorded human actions, one set containing manner actions and one set containing result actions, and then tested it by letting a human performer carry out the actions online in real time in front of the system’s 3D-camera. The system successfully recognized more than 94% of the manner actions and most of the result actions carried out by the human performer.}},
  author       = {{Gharaee, Zahra and Gärdenfors, Peter and Johnsson, Magnus}},
  booktitle    = {{12th International Conference on Signal Image Technology & Internet-Based Systems : SITIS 2016. Proceedings.}},
  isbn         = {{978-1-5090-5698-9}},
  language     = {{eng}},
  pages        = {{538--544}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Action Recognition Online with Hierarchical Self-Organizing Maps}},
  url          = {{http://dx.doi.org/10.1109/SITIS.2016.91}},
  doi          = {{10.1109/SITIS.2016.91}},
  year         = {{2016}},
}