Abstract
Studies in human-human interaction have introduced the concept of F-formation to describe the spatial organization of participants during social interaction. This paper aims at detecting such F-formations in images of video sequences. The proposed approach combines a voting scheme in the visual field of each participant and a memory process to make the detection in each frame robust to small, irrelevant changes of participant’s behavior. Results on the MatchNMingle data set demonstrate the good performances of this approach.
This work was partly supported by the chair of I. Bloch in Artificial Intelligence (Sorbonne Université and SCAI).
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Acknowledgments
The experiments in this paper used the MatchNMingle Dataset made available by the Delft University of Technology, Delft, The Netherlands [2].
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Fortier, V., Bloch, I., Pélachaud, C. (2022). Robust Detection of Conversational Groups Using a Voting Scheme and a Memory Process. In: El Yacoubi, M., Granger, E., Yuen, P.C., Pal, U., Vincent, N. (eds) Pattern Recognition and Artificial Intelligence. ICPRAI 2022. Lecture Notes in Computer Science, vol 13364. Springer, Cham. https://doi.org/10.1007/978-3-031-09282-4_14
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