Characterization of postures to analyze people’s emotions using kinect technology

Julián Alberto Monsalve-Pulido, Carlos Alberto Parra-Rodríguez

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This article synthesizes the research undertaken into the use of classification techniques that characterize people's positions, the objective being to identify emotions (astonishment, anger, happiness and sadness). We used a three-phase exploratory research methodology, which resulted in technological appropriation and a model that classified people’s emotions (in standing position) using the Kinect Skeletal Tracking algorithm, which is a free software. We proposed a feature vector for pattern recognition using classification techniques such as SVM, KNN, and Bayesian Networks for 17,882 pieces of data that were obtained in a 14-person training sample. As a result, we found that that the KNN algorithm has a maximum effectiveness of 89.0466%, which surpasses the other selected algorithms.

Translated title of the contributionCaracterización de posturas para el análisis de emociones de personas, por medio de la tecnología kinect
Original languageEnglish
Pages (from-to)256-263
Number of pages8
JournalDYNA (Colombia)
Volume85
Issue number205
DOIs
StatePublished - 01 Apr 2018

Keywords

  • Analysis of emotions
  • Free software
  • KNN
  • Kinect
  • Recognition of postures

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