Publicação
Gaussian Random Vector Fields in Trajectory Modelling
| Resumo: | This paper proposes the use of Gaussian random vector fields as a generative model to describe a set of observed trajectories in a 2-dimensional space. The observed trajectories are sequences of points in space sampled from continuous trajectories that are assumed to have been generated by an underlying velocity field. Given the observed velocities connecting the trajectory points, a vector field is obtained by condition- ing a Gaussian random vector field. Some results obtained in simulation are presented. |
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| Autores principais: | Barão, Miguel |
| Outros Autores: | Marques, Jorge S. |
| Assunto: | random fields pedestrian surveillance |
| Ano: | 2018 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade de Évora |
| Idioma: | inglês |
| Origem: | Repositório Científico da Universidade de Évora |
| Resumo: | This paper proposes the use of Gaussian random vector fields as a generative model to describe a set of observed trajectories in a 2-dimensional space. The observed trajectories are sequences of points in space sampled from continuous trajectories that are assumed to have been generated by an underlying velocity field. Given the observed velocities connecting the trajectory points, a vector field is obtained by condition- ing a Gaussian random vector field. Some results obtained in simulation are presented. |
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