### Abstract

surveillance scenario whether a person is walking or running and in what rough direction. The second problem is concerned with the recovery of action primitives from observed complex actions. Both problems will be discussed within a statistical framework. Bayesian propagation over time offers a framework to treat likelihood observations at each time step and the dynamics between the time steps in a unified manner. The first problem will be approached as a patter recognition and tracking task by a Bayesian propagation of the likelihoods. The latter problem will be

approached by explicitly specifying the dynamics while the likelihood measure will give a measure how good each dynamical model fit at each time step. Extensive experimental results show the applicability of the Bayesian framework for action recognition and round up our discussion.

Original language | English |
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Title of host publication | Human Motion : Understanding, Modelling, Capture and Animation |

Editors | B Rosenhahn, R Klette, D Metaxas |

Number of pages | 25 |

Place of Publication | Heidelberg |

Publisher | IEEE Computer Society Press |

Publication date | 2007 |

ISBN (Print) | 978-1-4020-6692-4 |

Publication status | Published - 2007 |

Series | Computational Imaging and Vision |
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Number | 36 |

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### Cite this

*Human Motion: Understanding, Modelling, Capture and Animation*Heidelberg: IEEE Computer Society Press. Computational Imaging and Vision, No. 36

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*Human Motion: Understanding, Modelling, Capture and Animation.*IEEE Computer Society Press, Heidelberg, Computational Imaging and Vision, no. 36.

**Recognition of Action as a Bayesian Parameter Estimation Problem over Time.** / Krüger, Volker.

Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review

TY - CHAP

T1 - Recognition of Action as a Bayesian Parameter Estimation Problem over Time

AU - Krüger, Volker

PY - 2007

Y1 - 2007

N2 - In this paper we will discuss two problems related to action recognition: The first problem is the one of identifying in asurveillance scenario whether a person is walking or running and in what rough direction. The second problem is concerned with the recovery of action primitives from observed complex actions. Both problems will be discussed within a statistical framework. Bayesian propagation over time offers a framework to treat likelihood observations at each time step and the dynamics between the time steps in a unified manner. The first problem will be approached as a patter recognition and tracking task by a Bayesian propagation of the likelihoods. The latter problem will be approached by explicitly specifying the dynamics while the likelihood measure will give a measure how good each dynamical model fit at each time step. Extensive experimental results show the applicability of the Bayesian framework for action recognition and round up our discussion.

AB - In this paper we will discuss two problems related to action recognition: The first problem is the one of identifying in asurveillance scenario whether a person is walking or running and in what rough direction. The second problem is concerned with the recovery of action primitives from observed complex actions. Both problems will be discussed within a statistical framework. Bayesian propagation over time offers a framework to treat likelihood observations at each time step and the dynamics between the time steps in a unified manner. The first problem will be approached as a patter recognition and tracking task by a Bayesian propagation of the likelihoods. The latter problem will be approached by explicitly specifying the dynamics while the likelihood measure will give a measure how good each dynamical model fit at each time step. Extensive experimental results show the applicability of the Bayesian framework for action recognition and round up our discussion.

M3 - Book chapter

SN - 978-1-4020-6692-4

BT - Human Motion

A2 - Rosenhahn, B

A2 - Klette, R

A2 - Metaxas, D

PB - IEEE Computer Society Press

CY - Heidelberg

ER -