针对电子游戏和元宇宙化身的面部情绪识别，特征集有所减少

IF 0.9 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Computer Animation and Virtual Worlds Pub Date : 2024-04-02 DOI:10.1002/cav.2230

Darren Bellenger, Minsi Chen, Zhijie Xu

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引用次数: 0

摘要

本文介绍了一种新颖的实时面部特征提取算法，该算法能生成一个小的特征集，适用于通过在线游戏和元宇宙化身实现情感识别。该算法旨在降低数据传输和存储要求，这些都是在这些媒体中采用情感识别的障碍。初步结果显示，在一个基准数据集上，面部情绪识别的准确率高达 92%，在各种数据集上的总体准确率为 77.2%，这表明了这项研究的早期前景。

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Facial emotion recognition with a reduced feature set for video game and metaverse avatars

This paper presents a novel real-time facial feature extraction algorithm, producing a small feature set, suitable for implementing emotion recognition with online game and metaverse avatars. The algorithm aims to reduce data transmission and storage requirements, hurdles in the adoption of emotion recognition in these mediums. The early results presented show a facial emotion recognition accuracy of up to 92% on one benchmark dataset, with an overall accuracy of 77.2% across a wide range of datasets, demonstrating the early promise of the research.

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来源期刊

Computer Animation and Virtual Worlds 工程技术-计算机：软件工程

CiteScore

2.20

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： With the advent of very powerful PCs and high-end graphics cards, there has been an incredible development in Virtual Worlds, real-time computer animation and simulation, games. But at the same time, new and cheaper Virtual Reality devices have appeared allowing an interaction with these real-time Virtual Worlds and even with real worlds through Augmented Reality. Three-dimensional characters, especially Virtual Humans are now of an exceptional quality, which allows to use them in the movie industry. But this is only a beginning, as with the development of Artificial Intelligence and Agent technology, these characters will become more and more autonomous and even intelligent. They will inhabit the Virtual Worlds in a Virtual Life together with animals and plants.

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