  Sports video analysis is a widespread research topic. Its applications are
very diverse, like events detection during a match, video summary, or
fine-grained movement analysis of athletes. As part of the MediaEval 2022
benchmarking initiative, this task aims at detecting and classifying subtle
movements from sport videos. We focus on recordings of table tennis matches.
Conducted since 2019, this task provides a classification challenge from
untrimmed videos recorded under natural conditions with known temporal
boundaries for each stroke. Since 2021, the task also provides a stroke
detection challenge from unannotated, untrimmed videos. This year, the
training, validation, and test sets are enhanced to ensure that all strokes are
represented in each dataset. The dataset is now similar to the one used in [1,
2]. This research is intended to build tools for coaches and athletes who want
to further evaluate their sport performances.
