通过整合拉班动作分析实现身体表达的情感理解
Bodily expressed emotion understanding through integrating Laban movement analysis
AI总结：
本研究基于Laban Movement Analysis动作编码系统构建高质量人类动作元素数据集，通过联合学习动作元素与情感，推动跨学科的身体语言情感自动理解与分析。
摘要：
身体动作携带有关个人情感或心理状态的重要信息，在日常沟通中不可或缺。增强机器理解通过身体语言表达的情感的能力，可以改善辅助机器人与儿童和老年用户的沟通，为精神科专业人员提供定量诊断和预后辅助，并协助执法部门识别欺骗。本研究基于Laban Movement Analysis动作编码系统开发了一个高质量的人类动作元素数据集，并利用该数据集联合学习动作元素与情感。我们的长期目标是整合计算科学、心理学和表演艺术的知识，以实现通过身体语言对情感和心理状态的自动化理解与分析。这项工作为进一步通过分析人类动作来识别情感的研究奠定了基础。
英文摘要：
Body movements carry important information about a person's emotions or mental state and are essential in daily communication. Enhancing the ability of machines to understand emotions expressed through body language can improve the communication of assistive robots with children and elderly users, provide psychiatric professionals with quantitative diagnostic and prognostic assistance, and aid law enforcement in identifying deception. This study develops a high-quality human motor element dataset based on the Laban Movement Analysis movement coding system and utilizes that to jointly learn about motor elements and emotions. Our long-term ambition is to integrate knowledge from computing, psychology, and performing arts to enable automated understanding and analysis of emotion and mental state through body language. This work serves as a launchpad for further research into recognizing emotions through analysis of human movement.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
