Real Time Emotion Analysis Using Deep Learning for Education, Entertainment, and Beyond

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Khuntia, Abhilash, Kale, Shubham
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866916313574670336
author Khuntia, Abhilash
Kale, Shubham
author_facet Khuntia, Abhilash
Kale, Shubham
contents The significance of emotion detection is increasing in education, entertainment, and various other domains. We are developing a system that can identify and transform facial expressions into emojis to provide immediate feedback.The project consists of two components. Initially, we will employ sophisticated image processing techniques and neural networks to construct a deep learning model capable of precisely categorising facial expressions. Next, we will develop a basic application that records live video using the camera on your device. The app will utilise a sophisticated model to promptly analyse facial expressions and promptly exhibit corresponding emojis.Our objective is to develop a dynamic tool that integrates deep learning and real-time video processing for the purposes of online education, virtual events, gaming, and enhancing user experience. This tool enhances interactions and introduces novel emotional intelligence technologies.
format Preprint
id arxiv_https___arxiv_org_abs_2407_04560
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Real Time Emotion Analysis Using Deep Learning for Education, Entertainment, and Beyond
Khuntia, Abhilash
Kale, Shubham
Computer Vision and Pattern Recognition
The significance of emotion detection is increasing in education, entertainment, and various other domains. We are developing a system that can identify and transform facial expressions into emojis to provide immediate feedback.The project consists of two components. Initially, we will employ sophisticated image processing techniques and neural networks to construct a deep learning model capable of precisely categorising facial expressions. Next, we will develop a basic application that records live video using the camera on your device. The app will utilise a sophisticated model to promptly analyse facial expressions and promptly exhibit corresponding emojis.Our objective is to develop a dynamic tool that integrates deep learning and real-time video processing for the purposes of online education, virtual events, gaming, and enhancing user experience. This tool enhances interactions and introduces novel emotional intelligence technologies.
title Real Time Emotion Analysis Using Deep Learning for Education, Entertainment, and Beyond
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2407.04560