Abstract
An overview of the group activity record is useful to facilitate review for self-reflection and improvement of the activity design. To obtain such a supplemental view for the group activity analysis, this study addresses estimating the unique scales for the target group activity in a data-driven manner, which complementary works with the existing knowledge-based measurement scales. In the proposed method, each ``scene'' in the group activity is represented by frequencies of ``elementary interactions'' occurring in the scene, and the whole group activity is defined by a collection of the scenes. Corresponding them to the relationship between ``document'' and ``word'' in a topic model for text analysis, Latent Dirichilet Allocation (LDA) is employed to estimate latent topics as the unique scales for the target group activity and the temporal transitions of the activity in the topic space. Instead of commonly used low-level features such as visual/motion patterns, the elementary interactions with a little semantics are used as codewords to simplify the interpretation of the estimated unique scales. To explore the feasibility of the proposed method, we performed qualitative analysis of the small group activities using their estimated unique scales and temporal transitions. We confirmed that they are helpful to analyze what activity patterns were formed, how they changed over time during the group activities, and how they were similar/different between two groups.
https://ror.org/02kpeqv85 
