A new approach for dynamic gesture recognition using skeleton trajectory representation and histograms of cumulative magnitudes

Edwin Escobedo, Guillermo Camara

Producción científica: Capítulo del libro/informe/acta de congresoArticulo (Contribución a conferencia)revisión exhaustiva

29 Citas (Scopus)

Resumen

In this paper, we present a new approach for dynamic hand gesture recognition that uses intensity, depth, and skeleton joint data captured by Kinect sensor. This method integrates global and local information of a dynamic gesture. First, we represent the skeleton 3D trajectory in spherical coordinates. Then, we select the most relevant points in the hand trajectory with our proposed method for keyframe detection. After, we represent the joint movements by spatial, temporal and hand position changes information. Next, we use the direction cosines definition to describe the body positions by generating histograms of cumulative magnitudes from the depth data which were converted in a point-cloud. We evaluate our approach with different public gesture datasets and a sign language dataset created by us. Our results outperformed state-of-the-art methods and highlight the smooth and fast processing for feature extraction being able to be implemented in real time.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2016
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas209-216
Número de páginas8
ISBN (versión digital)9781509035687
DOI
EstadoPublicada - 10 ene. 2017
Publicado de forma externa
Evento29th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2016 - Sao Jose dos Campos, Sao Paulo, Brasil
Duración: 4 oct. 20167 oct. 2016

Serie de la publicación

NombreProceedings - 2016 29th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2016

Conferencia

Conferencia29th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2016
País/TerritorioBrasil
CiudadSao Jose dos Campos, Sao Paulo
Período4/10/167/10/16

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