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 contribution | Caracterización de posturas para el análisis de emociones de personas, por medio de la tecnología kinect |
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Original language | English |
Pages (from-to) | 256-263 |
Number of pages | 8 |
Journal | DYNA (Colombia) |
Volume | 85 |
Issue number | 205 |
DOIs | |
State | Published - 01 Apr 2018 |
Keywords
- Analysis of emotions
- Free software
- KNN
- Kinect
- Recognition of postures