Netflix Control Method Using Smartwatches and Continuous Gesture Recognition

Abstract

This work proposes and evaluates a method for interaction and control of Netflix using continuous recognition of gestures in smartwatches. This method allows the user to pause, resume, rewind, move forward, increase and decrease the volume of the Netflix player using gestures similar to traditional icons for these tasks. The recognition of gestures is done using the algorithm of continuous recognition of gestures, so it is possible to recognize a gesture before it is finalized, in this way, it is possible to perform the action quickly thus improving the feedback to the user. We have developed a prototype for smartwatches that communicates with a communication platform that receives the actions and is responsible for executing them on Netflix. When performing a gesture, the first step is to recognize it, in sequence, the gesture is sent to the interaction platform and, finally, the action related to the gesture is performed. We performed an experiment with users and a usability and experience test, the results show that the gestures proposed in the method are intuitive and that it has the potential to be used in a pleasant and satisfactory way by the users.

Publication
In Proceedings of 32nd IEEE Canadian Conference of Electrical and Computer Engineering (CCECE 2019)
Thamer Nascimento
Thamer Nascimento
PhD Student
and former Master’s Student

Fabrizzio Soares is bla bla bla.

Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.

Thyago Carvalho
Thyago Carvalho
PhD Student
and former Master’s Student

Fabrizzio Soares is bla bla bla.

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