<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The efficient human-machine interaction is an essential and current problem of computer science. The paper presents a gesture recognition method which applies optical flow calculation and an aggregation for obtaining a heatmap-like representation of the motion trajectories. After the overview of the image processing workflow, the paper introduces six symbols for providing some measurements. The described experiments show the robustness of the method against color, shape and time variance.</p></abstract>

The efficient human-machine interaction is an essential and current problem of computer science. The paper presents a gesture recognition method which applies optical flow calculation and an aggregation for obtaining a heatmap-like representation of the motion trajectories. After the overview of the image processing workflow, the paper introduces six symbols for providing some measurements. The described experiments show the robustness of the method against color, shape and time variance.

An Optical Flow-Based Gesture Recognition Method

University of Miskolc 3515 Miskolc-Egyetemváros

Acta Marisiensis. Seria Technologica

This work is licensed under the Creative Commons Attribution 4.0 Public License.

{"article-title":"An Optical Flow-Based Gesture Recognition Method"}

The efficient human-machine interaction is an essential and current problem of computer science. The paper presents a gesture recognition method which applies...

An Optical Flow-Based Gesture Recognition Method

Publié en ligne: 26 mai 2020

Pages: 22 - 26

DOI: https://doi.org/10.2478/amset-2020-0005

Mots clés
gesture recognition, optical flow, feature extraction, classification, human computer interaction

© 2020 Dániel Zoltán Nagy et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 Public License.

An Optical Flow-Based Gesture Recognition Method

Publié en ligne: 26 mai 2020

Pages: 22 - 26

DOI: https://doi.org/10.2478/amset-2020-0005

Mots clésgesture recognition, optical flow, feature extraction, classification, human computer interaction

© 2020 Dániel Zoltán Nagy et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Mots clés
gesture recognition, optical flow, feature extraction, classification, human computer interaction