Human-computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns

Maqueda, Ana I. and Blanco Adán, Carlos Roberto del and García Santos, Narciso and Jaureguizar Núñez, Fernando (2015). Human-computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns. "Computer Vision and Image Understanding", v. 141 ; pp. 126-137. ISSN 1077-3142. https://doi.org/10.1016/j.cviu.2015.07.009.

Description

Title: Human-computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns
Author/s:
  • Maqueda, Ana I.
  • Blanco Adán, Carlos Roberto del
  • García Santos, Narciso
  • Jaureguizar Núñez, Fernando
Item Type: Article
Título de Revista/Publicación: Computer Vision and Image Understanding
Date: December 2015
Volume: 141
Subjects:
Freetext Keywords: Recognition; Hand gestures; Image descriptor; Video descriptor; Patterns; Segmentation; Spatio-temporal; LBP; SVM; Classification
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

A more natural, intuitive, user-friendly, and less intrusive Human–Computer interface for controlling an application by executing hand gestures is presented. For this purpose, a robust vision-based hand-gesture recognition system has been developed, and a new database has been created to test it. The system is divided into three stages: detection, tracking, and recognition. The detection stage searches in every frame of a video sequence potential hand poses using a binary Support Vector Machine classifier and Local Binary Patterns as feature vectors. These detections are employed as input of a tracker to generate a spatio-temporal trajectory of hand poses. Finally, the recognition stage segments a spatio-temporal volume of data using the obtained trajectories, and compute a video descriptor called Volumetric Spatiograms of Local Binary Patterns (VS-LBP), which is delivered to a bank of SVM classifiers to perform the gesture recognition. The VS-LBP is a novel video descriptor that constitutes one of the most important contributions of the paper, which is able to provide much richer spatio-temporal information than other existing approaches in the state of the art with a manageable computational cost. Excellent results have been obtained outperforming other approaches of the state of the art.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2010-20412UnspecifiedUnspecifiedUnspecified
Government of SpainTEC2013-48453UnspecifiedUnspecifiedUnspecified

More information

Item ID: 40737
DC Identifier: http://oa.upm.es/40737/
OAI Identifier: oai:oa.upm.es:40737
DOI: 10.1016/j.cviu.2015.07.009
Official URL: http://www.sciencedirect.com/science/article/pii/S1077314215001629
Deposited by: Memoria Investigacion
Deposited on: 06 Jun 2016 16:44
Last Modified: 01 Jan 2018 23:30
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