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Hierarchical Self-Organizing Maps System for Action Classification

Gharaee, Zahra LU ; Gärdenfors, Peter LU and Johnsson, Magnus LU (2017) ICAART 2017-International Conference on Agents and Artificial Intelligence p.583-590
Abstract
We present a novel action recognition system that is able to learn how to recognize and classify actions. Our system employs a three-layered hierarchy of Self-Organizing Maps together with a supervised neural network for labelling the actions. We have evaluated our system in an experiments consisting of ten different actions from a publicly available data set. The results are encouraging with 83% correctly classified actions based on the actor’s spatial trajectory.
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
Proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART 2017)
pages
8 pages
publisher
SciTePress
conference name
ICAART 2017-International Conference on Agents and Artificial Intelligence
conference location
Porto, Portugal
conference dates
2017-02-24 - 2017-02-26
external identifiers
  • wos:000413244200062
  • scopus:85049658703
ISBN
978-989-758-220-2
DOI
10.5220/0006199305830590
project
Ikaros: An infrastructure for system level modelling of the brain
Thinking in Time: Cognition, Communication and Learning
language
English
LU publication?
yes
id
98c8370a-8170-4acb-918e-37cb31933e8b
date added to LUP
2016-12-04 17:31:13
date last changed
2022-03-02 03:09:23
@inproceedings{98c8370a-8170-4acb-918e-37cb31933e8b,
  abstract     = {{We present a novel action recognition system that is able to learn how to recognize and classify actions. Our system employs a three-layered hierarchy of Self-Organizing Maps together with a supervised neural network for labelling the actions. We have evaluated our system in an experiments consisting of ten different actions from a publicly available data set. The results are encouraging with 83% correctly classified actions based on the actor’s spatial trajectory.}},
  author       = {{Gharaee, Zahra and Gärdenfors, Peter and Johnsson, Magnus}},
  booktitle    = {{Proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART 2017)}},
  isbn         = {{978-989-758-220-2}},
  language     = {{eng}},
  pages        = {{583--590}},
  publisher    = {{SciTePress}},
  title        = {{Hierarchical Self-Organizing Maps System for Action Classification}},
  url          = {{http://dx.doi.org/10.5220/0006199305830590}},
  doi          = {{10.5220/0006199305830590}},
  year         = {{2017}},
}