View Invariant Gesture Recognition using 3D Motion Primitives

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

21 Citationer (Scopus)

Resumé

This paper presents a method for automatic recognition of human gestures. The method works with 3D image data from a range camera to achieve invariance to viewpoint. The recognition is based solely on motion from characteristic instances of the gestures. These instances are denoted 3D motion primitives. The method extracts 3D motion from range images and represent the motion from each input frame in a view invariant manner using harmonic shape context. The harmonic shape context is classified as a 3D motion primitive. A sequence of input frames results in a set of primitives that are classified as a gesture using a probabilistic edit distance method. The system has been trained on frontal images (0deg camera rotation) and tested on 240 video sequences from 0deg and 45deg. An overall recognition rate of 82.9% is achieved. The recognition rate is independent of the viewpoint which shows that the method is indeed view invariant.
OriginalsprogEngelsk
TidsskriftProceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing
Sider (fra-til)797-800
ISSN1520-6149
DOI
StatusUdgivet - 2008
BegivenhedIEEE International Conference on Acoustics, Speech, and Signal Processing - Las Vegas, USA
Varighed: 31 mar. 20084 apr. 2008

Konference

KonferenceIEEE International Conference on Acoustics, Speech, and Signal Processing
LandUSA
ByLas Vegas
Periode31/03/200804/04/2008

Citer dette

@inproceedings{738ed5c06ad211dd92a2000ea68e967b,
title = "View Invariant Gesture Recognition using 3D Motion Primitives",
abstract = "This paper presents a method for automatic recognition of human gestures. The method works with 3D image data from a range camera to achieve invariance to viewpoint. The recognition is based solely on motion from characteristic instances of the gestures. These instances are denoted 3D motion primitives. The method extracts 3D motion from range images and represent the motion from each input frame in a view invariant manner using harmonic shape context. The harmonic shape context is classified as a 3D motion primitive. A sequence of input frames results in a set of primitives that are classified as a gesture using a probabilistic edit distance method. The system has been trained on frontal images (0deg camera rotation) and tested on 240 video sequences from 0deg and 45deg. An overall recognition rate of 82.9{\%} is achieved. The recognition rate is independent of the viewpoint which shows that the method is indeed view invariant.",
author = "Holte, {Michael Boelstoft} and Moeslund, {Thomas B.}",
year = "2008",
doi = "10.1109/ICASSP.2008.4517730",
language = "English",
pages = "797--800",
journal = "I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings",
issn = "1520-6149",
publisher = "IEEE Signal Processing Society",

}

TY - GEN

T1 - View Invariant Gesture Recognition using 3D Motion Primitives

AU - Holte, Michael Boelstoft

AU - Moeslund, Thomas B.

PY - 2008

Y1 - 2008

N2 - This paper presents a method for automatic recognition of human gestures. The method works with 3D image data from a range camera to achieve invariance to viewpoint. The recognition is based solely on motion from characteristic instances of the gestures. These instances are denoted 3D motion primitives. The method extracts 3D motion from range images and represent the motion from each input frame in a view invariant manner using harmonic shape context. The harmonic shape context is classified as a 3D motion primitive. A sequence of input frames results in a set of primitives that are classified as a gesture using a probabilistic edit distance method. The system has been trained on frontal images (0deg camera rotation) and tested on 240 video sequences from 0deg and 45deg. An overall recognition rate of 82.9% is achieved. The recognition rate is independent of the viewpoint which shows that the method is indeed view invariant.

AB - This paper presents a method for automatic recognition of human gestures. The method works with 3D image data from a range camera to achieve invariance to viewpoint. The recognition is based solely on motion from characteristic instances of the gestures. These instances are denoted 3D motion primitives. The method extracts 3D motion from range images and represent the motion from each input frame in a view invariant manner using harmonic shape context. The harmonic shape context is classified as a 3D motion primitive. A sequence of input frames results in a set of primitives that are classified as a gesture using a probabilistic edit distance method. The system has been trained on frontal images (0deg camera rotation) and tested on 240 video sequences from 0deg and 45deg. An overall recognition rate of 82.9% is achieved. The recognition rate is independent of the viewpoint which shows that the method is indeed view invariant.

U2 - 10.1109/ICASSP.2008.4517730

DO - 10.1109/ICASSP.2008.4517730

M3 - Conference article in Journal

SP - 797

EP - 800

JO - I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings

JF - I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings

SN - 1520-6149

ER -