Modeling and Classifying Human Activities From Trajectories Using a Class of Space-Varying Parametric Motion Fields

Abstract

Many approaches to trajectory analysis, such as clustering or classification, use probabilistic generative models, thus not requiring trajectory alignment/registration. Switched linear dynamical models (e.g., HMMs) have been used in this context, due to their ability to describe different motion regimes. However, these models are not suitable for handling… (More)
DOI: 10.1109/TIP.2013.2244607

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@article{Nascimento2013ModelingAC, title={Modeling and Classifying Human Activities From Trajectories Using a Class of Space-Varying Parametric Motion Fields}, author={Jacinto C. Nascimento and Jorge S. Marques and Jo{\~a}o Miranda Lemos}, journal={IEEE Transactions on Image Processing}, year={2013}, volume={22}, pages={2066-2080} }