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Found 2 papers, 2 papers with code
Pose2Gait: Extracting Gait Features from Monocular Video of Individuals with Dementia
In this work we train a deep neural network to map from a two dimensional pose sequence, extracted from a video of an individual walking down a hallway toward a wall-mounted camera, to a set of three-dimensional spatiotemporal gait features averaged over the walking sequence.
Tracking by weakly-supervised learning and graph optimization for whole-embryo C. elegans lineages
Our work specifically addresses the following challenging properties of C. elegans embryo recordings: (1) Many cell divisions as compared to benchmark recordings of other organisms, and (2) the presence of polar bodies that are easily mistaken as cell nuclei.
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