多视图情绪表达数据集使用2D姿势估计数据集
Mingming Zhang1,2, Yanan Zhou1,2, Xinye Xu1,2
1Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, Liaoning, China.
Scientific data
|September 22, 2023
概括
本研究介绍了多视图情绪表达数据集 (MEED),这是一个大集合的2D视频捕捉自然的人体语言和情绪. MEED为推进情感计算和人机交互研究提供了关键数据.
科学领域:
- 计算机科学 计算机科学
- 心理学 心理学 心理学
- 神经科学是一个神经科学.
背景情况:
- 人体表情对于传达情绪和意图至关重要,往往超过了口头交流.
- 现有的身体表情数据集主要使用运动捕捉,缺乏自然主义的2D视频数据.
- 需要可访问的,大规模的自然肢体语言数据集用于研究.
研究的目的:
- 介绍多视图情绪表达数据集 (MEED),这是研究肢体语言的新资源.
- 通过2D视频捕获的自然化情感身体表达的综合数据集.
- 促进对情感计算,人机交互和相关领域的研究.
主要方法:
- 收集了22位演员的4102个视频,显示了6种情绪 (愤怒,厌恶,恐惧,快乐,悲伤,惊喜) 和中性表情.
- 从三个角度记录运动:左,正面和右.
- 使用2D姿势估计生成相应的姿势数据 (397,809个PNG和JSON文件).
主要成果:
- 多视图情绪表达数据集 (MEED) 包含超过150GB的数据.
- 包括不同情绪表达的同步视频和2D姿势估计数据.
- 为人类情感肢体语言的计算分析提供了丰富的资源.
结论:
- MEED解决了随时可用的,自然主义的2D身体表达数据集的缺口.
- 该数据集预计将显著有利于在情感计算,HCI,社会神经科学和精神病学方面的研究.
- 促进了更复杂的情绪识别系统和以人为中心的AI的发展.
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