Evaluación de modelos para el reconocimiento de gestos en señales biométricas, para un usuario con movilidad reducida. Cabezas, H. S. & Sarmiento, W. J. TecnoLógicas, 22:33–47, December, 2019. ![Evaluación de modelos para el reconocimiento de gestos en señales biométricas, para un usuario con movilidad reducida [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex This paper compares the results of three computational models (pattern recognition, hidden Markov models, and bag of features) for recognizing the hand gestures of a user with reduced mobility using biometric signal processing. The evaluation of the models included eight gestures co-designed with a person with reduced mobility. The models were evaluated using a cross-validation scheme, calculating sensitivity and precision metrics, and a data set of ten repetitions of each gesture. It can be concluded that the bag-of-features model achieved the best performance considering the two metrics under evaluation; the traditional pattern recognition model, using vector support machines, produced the most stable results; and the hidden Markov models had the lowest performance.
@article{cabezas_evaluacion_2019,
title = {Evaluación de modelos para el reconocimiento de gestos en señales biométricas, para un usuario con movilidad reducida},
volume = {22},
copyright = {Copyright (c)},
issn = {2256-5337},
url = {https://revistas.itm.edu.co/index.php/tecnologicas/article/view/1513},
doi = {10.22430/22565337.1513},
abstract = {This paper compares the results of three computational models (pattern recognition, hidden Markov models, and bag of features) for recognizing the hand gestures of a user with reduced mobility using biometric signal processing. The evaluation of the models included eight gestures co-designed with a person with reduced mobility. The models were evaluated using a cross-validation scheme, calculating sensitivity and precision metrics, and a data set of ten repetitions of each gesture. It can be concluded that the bag-of-features model achieved the best performance considering the two metrics under evaluation; the traditional pattern recognition model, using vector support machines, produced the most stable results; and the hidden Markov models had the lowest performance.},
language = {es},
urldate = {2022-06-09},
journal = {TecnoLógicas},
author = {Cabezas, Holman S. and Sarmiento, Wilson J.},
month = dec,
year = {2019},
keywords = {Gesture recognition, Human computer interaction, Machine learning, Pattern recognition, Signal processing},
pages = {33--47},
}
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