虚拟现实环境中的面部表情识别:挑战和机遇
Zhihui Zhang1, Josep M Fort1, Lluis Giménez Mateu1
1Escola Tècnica Superior d'Arquitectura de Barcelona, Universitat Politècnica de Catalunya, Barcelona, Spain.
Frontiers in psychology
|October 27, 2023
概括
在虚拟现实 (VR) 中面部情绪识别显示出有前途,对于基本情绪具有很高的准确性. 然而,像愤怒和恐惧这样的高级情绪仍然是当前系统的挑战.
科学领域:
- 计算机科学 计算机科学
- 人与计算机的交互
- 心理学 心理学 心理学
背景情况:
- 面部情绪识别 (FER) 对于理解虚拟现实 (VR) 中的用户体验至关重要.
- 现有的FER系统在动态VR环境中准确检测微妙的情绪方面面临挑战.
研究的目的:
- 评估使用MobileNet V2在虚拟现实环境中的新型面部情绪识别系统的有效性.
- 识别准确识别的特定情绪和那些对系统构成挑战的情绪.
主要方法:
- 一个轻量级的卷积神经网络,MobileNet V2,用于情绪检测.
- 该系统在15名大学生上进行了测试,他们在虚拟现实环境中进行互动.
- 基于对各种面部表情的识别率来评估表现.
主要成果:
- 对于"中立"",快乐"",悲伤"和"惊喜"情绪,实现了高识别率.
- 该系统对"愤怒"和"恐惧"的准确性较低,经常将它们错误地归类为"中立".
- 差异可能与重叠的面部线索,有限的训练数据和设备精度有关.
结论:
- 面部情绪识别技术对于虚拟现实应用是可行的.
- 未来的发展需要模型增强,优越的硬件,以及一种全面的情绪检测方法.
- 需要进一步的研究来提高VR中复杂情绪的准确性.
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