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

James Wang
Sarah Rajtmajer

Sponsoring Agency
National Science Foundation


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.

Research Area
Artificial Intelligence and Big Data
Human-Computer Interaction