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@inproceedings{maman-2020-DC-ICMI,
author = {Maman, Lucien},
title = {Multimodal Groups' Analysis for Automated Cohesion Estimation},
year = {2020},
isbn = {9781450375818},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3382507.3421153},
doi = {10.1145/3382507.3421153},
abstract = {Groups are getting more and more scholars' attention. With the rise of Social Signal Processing (SSP), many studies based on Social Sciences and Psychology findings focused on detecting and classifying groups? dynamics. Cohesion plays an important role in these groups? dynamics and is one of the most studied emergent states, involving both group motions and goals. This PhD project aims to provide a computational model addressing the multidimensionality of cohesion and capturing its subtle dynamics. It will offer new opportunities to develop applications to enhance interactions among humans as well as among humans and machines.},
booktitle = {Proceedings of the 2020 International Conference on Multimodal Interaction},
pages = {713–717},
numpages = {5},
keywords = {computational model, emergent state, dataset, multimodality, cohesion},
location = {Virtual Event, Netherlands},
series = {ICMI '20}
}