Motion Classification Based On Geometrical Features Of Trajectories
Résumé
This paper proposes a novel approach for motion clas-
sification based on geometrical features computed on tra-
jectories. The method follows a machine learning approach
trained and validated on synthetic datasets simulating several
stochastic models. The resulting model enables, in particular,
the recognition of different subdiffusive behaviors, offering a
finer classification than the standard method based on mean
square displacement. The method is assessed on a biological
dataset containing trajectories of CCR5 cell receptors.
Fichier principal
Motion_classification_based_on_geometrical_features_of_trajectories___ISBI2024.pdf (357.67 Ko)
Télécharger le fichier
Origine | Fichiers produits par l'(les) auteur(s) |
---|