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Using Hidden Markov Models for recognizing action primitives in complex actions

Krüger, Volker LU orcid and Grest, Daniel (2007) 15th Scandinavian Conference on Image Analysis, SCIA 2007 In Lecture Notes in Computer Science 4522. p.203-212
Abstract

There is biological evidence that human actions are composed out of action primitives, like words and sentences being composed out of phonemes. Similarly to language processing, one possibility to model and recognize complex actions is to use grammars with action primitives as the alphabet. A major challenge here is that the action primitives need to be recovered first from the noisy input signal before further processing with the action grammar can be done. In this paper we combine a Hidden Markov Model-based approach with a simplified version of a condensation algorithm which allows to recover the action primitives in an observed action. In our approach, the primitives may have different lengths, no clear "divider" between the... (More)

There is biological evidence that human actions are composed out of action primitives, like words and sentences being composed out of phonemes. Similarly to language processing, one possibility to model and recognize complex actions is to use grammars with action primitives as the alphabet. A major challenge here is that the action primitives need to be recovered first from the noisy input signal before further processing with the action grammar can be done. In this paper we combine a Hidden Markov Model-based approach with a simplified version of a condensation algorithm which allows to recover the action primitives in an observed action. In our approach, the primitives may have different lengths, no clear "divider" between the primitives is necessary. The primitive detection is done online, no storing of past data is required. We verify our approach on a large database. Recognition rates are slightly lower than the rate when recognizing the singular action primitives.

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author
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publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Image Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings
series title
Lecture Notes in Computer Science
volume
4522
pages
10 pages
conference name
15th Scandinavian Conference on Image Analysis, SCIA 2007
conference location
Aalborg, Denmark
conference dates
2007-06-10 - 2007-06-14
external identifiers
  • scopus:38049073867
ISSN
0302-9743
1611-3349
ISBN
9783540730392
DOI
10.1007/978-3-540-73040-8_21
language
English
LU publication?
no
id
4c73a69f-4eca-40cb-9d42-448b0cf36208
date added to LUP
2019-07-08 21:17:55
date last changed
2025-04-04 15:22:34
@inproceedings{4c73a69f-4eca-40cb-9d42-448b0cf36208,
  abstract     = {{<p>There is biological evidence that human actions are composed out of action primitives, like words and sentences being composed out of phonemes. Similarly to language processing, one possibility to model and recognize complex actions is to use grammars with action primitives as the alphabet. A major challenge here is that the action primitives need to be recovered first from the noisy input signal before further processing with the action grammar can be done. In this paper we combine a Hidden Markov Model-based approach with a simplified version of a condensation algorithm which allows to recover the action primitives in an observed action. In our approach, the primitives may have different lengths, no clear "divider" between the primitives is necessary. The primitive detection is done online, no storing of past data is required. We verify our approach on a large database. Recognition rates are slightly lower than the rate when recognizing the singular action primitives.</p>}},
  author       = {{Krüger, Volker and Grest, Daniel}},
  booktitle    = {{Image Analysis - 15th Scandinavian Conference, SCIA 2007, Proceedings}},
  isbn         = {{9783540730392}},
  issn         = {{0302-9743}},
  language     = {{eng}},
  month        = {{12}},
  pages        = {{203--212}},
  series       = {{Lecture Notes in Computer Science}},
  title        = {{Using Hidden Markov Models for recognizing action primitives in complex actions}},
  url          = {{http://dx.doi.org/10.1007/978-3-540-73040-8_21}},
  doi          = {{10.1007/978-3-540-73040-8_21}},
  volume       = {{4522}},
  year         = {{2007}},
}