CCRI: Planning: Planning to Develop a Body Language Dataset for the Artificial Intelligence Research Community

CCRI：规划：规划为人工智能研究界开发肢体语言数据集

• 批准号: 1921783
• 负责人: James Wang
• 金额: $ 10万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1921783&HistoricalAwards=false
• 关键词: CCRI; Planning; Develop; Body; Language

This CISE Community Research Infrastructure (CCRI) planning project aims to form a community of researchers galvanized around the creation of a very large scale, high-quality annotated video dataset for broad use by the affective computing community, especially for computational understanding of human bodily expressions in the wild. Computational understanding of body language for emotional expressions in real-world environments is a fundamental and challenging research topic. Breakthroughs in this technological area have the potential to enable a large number of innovative applications including personal assistant robot, social robot, and multimedia information retrieval. The planning project will encourage the scientific community to take a multidisciplinary and holistic approach to the problem of body language understanding. The project aims to gain deeper insights into useful data collection for computational and data-driven modeling of emotions based on body language. Ultimately, by analyzing and harnessing a large quantity of carefully-collected affective data, using state-of-the-art machine learning and statistical modeling methodologies, future intelligent systems can be empowered with new capabilities of understanding human emotions.This planning project will involve researchers in computer and information sciences, social and clinical psychology, statistics, and data ethics. A workshop will be organized in conjunction with one of the leading international conferences in the research area. The team will reach out to relevant communities to attract researchers to participate in the workshop. At the workshop, a data-driven emotion modeling competition will be organized using a preliminary dataset that the team has collected. Winning teams will be invited to present their results at the workshop. The workshop will also feature panels and discussion sessions to solicit input from the broader community on the design and implementation of the potential data infrastructure. The planning effort will result in a publication on the consensus reached at the workshop on the community's need for this data infrastructure and the detailed specifications on various aspects of the data collection effort.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该 CISE 社区研究基础设施 (CCRI) 规划项目旨在形成一个研究人员社区，围绕创建大规模、高质量带注释的视频数据集，供情感计算社区广泛使用，特别是对人体表达的计算理解在野外。对现实环境中情感表达的肢体语言的计算理解是一个基础且具有挑战性的研究课题。这一技术领域的突破有可能催生大量创新应用，包括个人助理机器人、社交机器人和多媒体信息检索。该规划项目将鼓励科学界采取多学科和整体的方法来解决肢体语言理解问题。该项目旨在更深入地了解有用的数据收集，用于基于肢体语言的计算和数据驱动的情感建模。最终，通过分析和利用大量精心收集的情感数据，使用最先进的机器学习和统计建模方法，未来的智能系统可以具有理解人类情感的新能力。该规划项目将涉及计算机和信息科学、社会和临床心理学、统计学和数据伦理学的研究人员。将与该研究领域领先的国际会议之一联合举办研讨会。该团队将联系相关社区，吸引研究人员参加研讨会。在研讨会上，将使用团队收集的初步数据集组织数据驱动的情感建模竞赛。获奖团队将被邀请在研讨会上展示他们的成果。该研讨会还将举办小组讨论和讨论会，以征求更广泛的社区对潜在数据基础设施的设计和实施的意见。规划工作将导致在研讨会上就社区对此数据基础设施的需求达成的共识以及数据收集工作各个方面的详细规范发表一份出版物。该奖项反映了 NSF 的法定使命，并被认为值得通过以下方式获得支持：使用基金会的智力价值和更广泛的影响审查标准进行评估。

项目成果

Modeling Aesthetics and Emotions in Visual Content: From Vincent van Gogh to Robotics and Vision

视觉内容中的美学和情感建模：从文森特·梵高到机器人和视觉

• 发表时间: 2020-10
• 期刊: in conjunction with the ACM International Conference on Multimedia
• 作者: Wang; James Z.
• 通讯作者: James Z.

Bodily Expressed Emotion Understanding Research: A Multidisciplinary Perspective

身体表达的情绪理解研究：多学科视角

• 发表时间: 2020-08
• 期刊: Lecture Notes in Computer Science
• 作者: Wang, James Z.;Badler, Norman;Berthouze, Nadia;Gilmore, Rick O.;Johnson, Kerri L.;Lapedriza, Agata;Lu, Xin;Troje, Nikolaus
• 通讯作者: Troje, Nikolaus

MEBOW: Monocular Estimation of Body Orientation In the Wild

MEBOW：野外身体方向的单目估计

• DOI: 10.1109/cvpr42600.2020.00351
• 发表时间: 2020-06
• 期刊: IEEE Conference on Computer Vision and Pattern Recognition
• 作者: Wu, Chenyan;Chen, Yukun;Luo, Jiajia;Su, Che;Hanzra, Bikramjot;Deng, Zhuo;Liu, Bilan;Wang, James Z.;Kuo, Cheng
• 通讯作者: Kuo, Cheng