Publication Date

Spring 2022

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Chris Tseng

Second Advisor

Ching-Seh Wu

Third Advisor

Nikhil Hiremath

Keywords

Neural Networks, Computer Vision, Gesture Recognition, Time-Series Classification.

Abstract

The advances in technology have brought in a lot of changes in the way humans go about their lives. This has enhanced the significance of Artificial Neural Networks and Computer Vision- based interactions with the world. Gesture Recognition is one of the major focus areas in Computer Vision. This involves Human Computer Interfaces (HCI) that would capture and understand human actions. In this project, we will explore how Neural Network concepts can be applied in this challenging field of Computer Vision. By leveraging the latest research for Gesture Recognition, we researched on how to capture the movement across different frames of the gestures in videos. We experimented on preprocessed 2D and 3D data by applying various Neural Network models such as Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) using Time Series Classification Technique to recognize the Gesture.

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