AUTOMATIC ANALYSIS OF TIMING AND SYNCHRONY IN ROWING
Date
2025-05
Authors
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Journal ISSN
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Publisher
University of Delaware
Abstract
Synchrony and Timing are key components of the sport of rowing. This thesis
investigated different ways of determining the synchrony between two athletes on
rowing ergometers in a video. First, human pose estimation techniques were used to
extract body key points and compare the synchrony of one or multiple body parts across
the length of the video. Second, a video classification model based on either the R3D or
I3D model were trained to classify rowing videos as synchronized or unsynchronized
and their performance was compared.
The pose estimation approach could detect and highlight small asynchronies
between rowers that are hard to detect for humans and could provide valuable additions
to rowing training. For the video classification approaches, the R3D-based model
reliably classified rowing videos and generalized well to unseen and slightly different
data. It outperformed the I3D-based approach, which performed well on the training
data but generalized poorly to different data.