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Related Experiment Video

Updated: Jun 17, 2026

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Published on: March 14, 2017

A Smartphone-Based Cursor Position System in Cross-Device Interaction Using Machine Learning Techniques.

Juechen Yang¹, Jun Kong¹, Chunying Zhao²

¹Department of Computer Science, North Dakota State University, Fargo, ND 58105, USA.

Sensors (Basel, Switzerland)

|March 6, 2021

Summary

This summary is machine-generated.

This study introduces a novel system for seamless mobile and large display interaction. It uses a smartphone

Keywords:

cross-device interaction gestural interaction large display mobile device motion detection

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Area of Science:

Human-Computer Interaction
Mobile Computing
Ubiquitous Computing

Background:

Mobile devices, particularly smartphones, are increasingly prevalent.
There is a growing demand for interaction techniques that bridge mobile devices and large displays.
Existing methods often lack seamless integration and direct manipulation capabilities.

Purpose of the Study:

To develop a novel cross-device cursor position system.
To enable direct manipulation of large displays using mobile devices.
To facilitate seamless cross-device data sharing irrespective of physical proximity.

Main Methods:

Utilizing sound localization for initial cursor positioning on a large display.
Employing smartphone accelerometer data for movement detection.
Applying machine learning models to translate mobile device movements to cursor movements.

Main Results:

Successfully mapped mobile device movement to cursor movement on a large display.
Demonstrated direct object manipulation on large displays via mobile devices.
Identified gradient boosting, linear discriminant analysis (LDA), and naïve Bayes as effective classifiers for movement detection.

Conclusions:

The developed system enables intuitive cross-device interaction.
Machine learning significantly enhances the accuracy of mobile device movement translation.
The system offers a foundation for more integrated human-computer interaction paradigms.