The AffectMove 2021 Challenge - Affect Recognition from Naturalistic Movement Data
2021
We ran the first Affective Movement Recognition
(AffectMove) challenge that brings together datasets of affective
bodily behaviour across different real-life applications to foster
work in this area. Research on automatic detection of naturalistic
affective body expressions is still lagging behind detection based
on other modalities whereas movement behaviour modelling
is a very interesting and very relevant research problem for
the affective computing community. The AffectMove challenge
aimed to take advantage of existing body movement datasets
to address key research problems of automatic recognition of
naturalistic and complex affective behaviour from this type of
data. Participating teams competed to solve at least one of three
tasks based on datasets of different sensors types and reallife problems: multimodal EmoPain dataset for chronic pain
physical rehabilitation context, weDraw-1 Movement dataset
for maths problem solving settings, and multimodal UnigeMaastricht Dance dataset. To foster work across datasets, we
also challenged participants to take advantage of the data across
datasets to improve performances and also test the generalization
of their approach across different applications.
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