Deployable Solution for Real-Time Children Face Emotion Prediction System

Title

Deployable Solution for Real-Time Children Face Emotion Prediction System

Creator

Shivaprasad, D.L.; Guru, D.S.; Kavitha, R.

Description

Nowadays, many parents struggle to comprehend their children's emotions, which can hinder the creation of a nurturing environment. While numerous models focus on predicting adult emotions, there is a lack of standardised datasets for studying children's emotions. To address this gap, our work attempts to establish a comprehensive children's emotion dataset that can facilitate the study of emotions across various pose orientations. Furthermore, we propose an efficient and deployable system for real-time children's emotion prediction. An effective face detector with deep architecture is designed to handle all pose orientations from key image frames. Optimal features are then selected by re-ranking the features using a hybrid feature selection mechanism. The emotion category is declared by carefully analysing sequences of emotion identification from these features. This system holds promise for educational institutions and healthcare facilities, offering insights into children's behaviour through emotional analysis. Through experimental comparisons with three state-of-the-art emotion prediction models, we observed that our proposed system consistently outperforms existing models. Hence, we strongly recommend the adoption of our proposed system. With its achievement of state-of-the-art results in children's facial emotion recognition, it offers a practical solution for real-time deployment across diverse settings. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Source

Lecture Notes in Computer Science;Volume;15505 LNCS;pp.204-224

Date

01-01-2025

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Emotion Prediction; Hybrid Feature Selection; Key-frame Selection; Re-ranking

Coverage

Shivaprasad D.L., Department of Studies in Computer Science, University of Mysore, Mysuru, Manasagangotri, India; Guru D.S., Department of Studies in Computer Science, University of Mysore, Mysuru, Manasagangotri, India; Kavitha R., Department of Data Science, CHRIST (Deemed to be University), Bangalore, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 3029743; ISBN: 978-303184542-0;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-3-031-84543-7_17

https://www.scopus.com/pages/publications/105003637548?origin=resultslist