Motion Primitives for Action Recognition

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Resumé

The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognition rates of 88.7% and 85.5%, respectively.

OriginalsprogEngelsk
TitelGW 2007 : The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation
RedaktørerMiguel Sales Dias, Ricardo Jota
Antal sider2
ForlagADETTI/ISCTE
Publikationsdato2007
Sider14-15
ISBN (Trykt)9789728862053
StatusUdgivet - 2007
BegivenhedInternational Workshop on Gesture in Human-Computer Interaction and Simulation - Lisbon, Portugal
Varighed: 23 maj 200725 maj 2007
Konferencens nummer: 7

Konference

KonferenceInternational Workshop on Gesture in Human-Computer Interaction and Simulation
Nummer7
LandPortugal
ByLisbon
Periode23/05/200725/05/2007

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Fihl, P., Holte, M. B., & Moeslund, T. B. (2007). Motion Primitives for Action Recognition. I M. Sales Dias, & R. Jota (red.), GW 2007: The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation (s. 14-15). ADETTI/ISCTE.
Fihl, Preben ; Holte, Michael Boelstoft ; Moeslund, Thomas B. / Motion Primitives for Action Recognition. GW 2007: The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation. red. / Miguel Sales Dias ; Ricardo Jota. ADETTI/ISCTE, 2007. s. 14-15
@inproceedings{b3c69af00dc811dcb676000ea68e967b,
title = "Motion Primitives for Action Recognition",
abstract = "The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognition rates of 88.7{\%} and 85.5{\%}, respectively.",
keywords = "Gesture recognition, Motion primitives",
author = "Preben Fihl and Holte, {Michael Boelstoft} and Moeslund, {Thomas B.}",
year = "2007",
language = "English",
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Fihl, P, Holte, MB & Moeslund, TB 2007, Motion Primitives for Action Recognition. i M Sales Dias & R Jota (red), GW 2007: The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation. ADETTI/ISCTE, s. 14-15, International Workshop on Gesture in Human-Computer Interaction and Simulation, Lisbon, Portugal, 23/05/2007.

Motion Primitives for Action Recognition. / Fihl, Preben; Holte, Michael Boelstoft; Moeslund, Thomas B.

GW 2007: The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation. red. / Miguel Sales Dias; Ricardo Jota. ADETTI/ISCTE, 2007. s. 14-15.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - Motion Primitives for Action Recognition

AU - Fihl, Preben

AU - Holte, Michael Boelstoft

AU - Moeslund, Thomas B.

PY - 2007

Y1 - 2007

N2 - The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognition rates of 88.7% and 85.5%, respectively.

AB - The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognition rates of 88.7% and 85.5%, respectively.

KW - Gesture recognition

KW - Motion primitives

M3 - Article in proceeding

SN - 9789728862053

SP - 14

EP - 15

BT - GW 2007

A2 - Sales Dias, Miguel

A2 - Jota, Ricardo

PB - ADETTI/ISCTE

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Fihl P, Holte MB, Moeslund TB. Motion Primitives for Action Recognition. I Sales Dias M, Jota R, red., GW 2007: The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation. ADETTI/ISCTE. 2007. s. 14-15