Pedestrian tracking using probability fields and a movement feature space

"Retrieving useful information from video sequences, such as the dynamics of pedestrians, and other moving objects on a video sequence, leads to further knowledge of what is happening on a scene. In this paper, a Target Framework associates each person with an autonomous entity, modeling its tr...

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Detalles Bibliográficos
Autores principales: Negri, Pablo, Garayalde, Damián
Formato: Artículos de Publicaciones Periódicas publishedVersion
Lenguaje:Inglés
Publicado: 2019
Materias:
PEATONES
PROBABILIDAD
DINAMICA
SEGUIMIENTO
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/1639
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-1639
record_format dspace
spelling I32-R138-123456789-16392022-12-07T13:07:00Z Pedestrian tracking using probability fields and a movement feature space Negri, Pablo Garayalde, Damián PEATONES PROBABILIDAD DINAMICA SEGUIMIENTO "Retrieving useful information from video sequences, such as the dynamics of pedestrians, and other moving objects on a video sequence, leads to further knowledge of what is happening on a scene. In this paper, a Target Framework associates each person with an autonomous entity, modeling its trajectory and speed by using a state machine. The particularity of our methodology is the use of a Movement Feature Space (MFS) to generate descriptors for classifiers and trackers. This approach is applied to two public sequences (PETS2009 and TownCentre). The results of this tracking outperform other algorithms reported in the literature, which have, however, a higher computational complexity." 2019-07-10T13:52:40Z 2019-07-10T13:52:40Z 2017-12 Artículos de Publicaciones Periódicas info:eu-repo/semantics/publishedVersion 2346-2183 http://ri.itba.edu.ar/handle/123456789/1639 en info:eu-repo/semantics/reference/doi/10.15446/dyna.v84n200.57028 info:eu-repo/grantAgreement/ANPCyT/PICT/2283/AR. Ciudad Autónoma de Buenos Aires info:eu-repo/grantAgreement/UADE/ACyT/ A15T14/AR. Ciudad Autónoma de Buenos Aires info:eu-repo/grantAgreement/CONICET/AR. Ciudad Autónoma de Buenos Aires https://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic PEATONES
PROBABILIDAD
DINAMICA
SEGUIMIENTO
spellingShingle PEATONES
PROBABILIDAD
DINAMICA
SEGUIMIENTO
Negri, Pablo
Garayalde, Damián
Pedestrian tracking using probability fields and a movement feature space
topic_facet PEATONES
PROBABILIDAD
DINAMICA
SEGUIMIENTO
description "Retrieving useful information from video sequences, such as the dynamics of pedestrians, and other moving objects on a video sequence, leads to further knowledge of what is happening on a scene. In this paper, a Target Framework associates each person with an autonomous entity, modeling its trajectory and speed by using a state machine. The particularity of our methodology is the use of a Movement Feature Space (MFS) to generate descriptors for classifiers and trackers. This approach is applied to two public sequences (PETS2009 and TownCentre). The results of this tracking outperform other algorithms reported in the literature, which have, however, a higher computational complexity."
format Artículos de Publicaciones Periódicas
publishedVersion
author Negri, Pablo
Garayalde, Damián
author_facet Negri, Pablo
Garayalde, Damián
author_sort Negri, Pablo
title Pedestrian tracking using probability fields and a movement feature space
title_short Pedestrian tracking using probability fields and a movement feature space
title_full Pedestrian tracking using probability fields and a movement feature space
title_fullStr Pedestrian tracking using probability fields and a movement feature space
title_full_unstemmed Pedestrian tracking using probability fields and a movement feature space
title_sort pedestrian tracking using probability fields and a movement feature space
publishDate 2019
url http://ri.itba.edu.ar/handle/123456789/1639
work_keys_str_mv AT negripablo pedestriantrackingusingprobabilityfieldsandamovementfeaturespace
AT garayaldedamian pedestriantrackingusingprobabilityfieldsandamovementfeaturespace
_version_ 1765661092503093248

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