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http://hdl.handle.net/10071/29104
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Correia, S. | - |
dc.contributor.author | Mendes, D. | - |
dc.contributor.author | Jorge, P. | - |
dc.contributor.author | Brandão, T. | - |
dc.contributor.author | Arriaga, P. | - |
dc.contributor.author | Nunes, L. | - |
dc.date.accessioned | 2023-07-31T14:10:57Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Correia, S., Mendes, D., Jorge, P., Brandão, T., Arriaga, P., & Nunes, L. (2023). Occlusion-aware pedestrian detection and tracking. In 2023 30th International Conference on Systems, Signals and Image Processing (IWSSIP). IEEE. https://doi.org/10.1109/IWSSIP58668.2023.10180296 | - |
dc.identifier.isbn | 979-8-3503-3729-7 | - |
dc.identifier.issn | 2157-8672 | - |
dc.identifier.uri | http://hdl.handle.net/10071/29104 | - |
dc.description.abstract | This paper proposes an occlusion-aware mechanism, used on a framework for detecting and tracking pedestrians in videos acquired from surveillance cameras, which includes the extraction of trajectory points, estimation of walking velocities, detection of groups, and projection of the final trajectories into a 2D plan. The occlusion-aware mechanism is introduced in order to manage irregularities in the pedestrian trajectory data derived from occlusions. This mechanism is able to identify the parts of the human body that are occluded, using skeleton data generated by human pose estimation algorithms, and adjust the dimensions of the bounding boxes of the occluded pedestrians. | eng |
dc.language.iso | eng | - |
dc.publisher | IEEE | - |
dc.relation | LISBOA-01-0247-FEDER-04715 | - |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04466%2F2020/PT | - |
dc.relation.ispartof | 2023 30th International Conference on Systems, Signals and Image Processing (IWSSIP) | - |
dc.rights | embargoedAccess | - |
dc.subject | Object detection | eng |
dc.subject | Multi-object tracking | eng |
dc.subject | Trajectory extraction | eng |
dc.subject | Pose estimation | eng |
dc.subject | Computer vision | eng |
dc.subject | Deep learning | eng |
dc.title | Occlusion-aware pedestrian detection and tracking | eng |
dc.type | conferenceObject | - |
dc.event.title | 30th International Conference on Systems, Signals and Image Processing (IWSSIP) | - |
dc.event.type | Conferência | pt |
dc.event.location | Ohrid, North Macedonia | eng |
dc.event.date | 2023 | - |
dc.peerreviewed | yes | - |
dc.date.updated | 2023-07-31T15:07:42Z | - |
dc.description.version | info:eu-repo/semantics/acceptedVersion | - |
dc.identifier.doi | 10.1109/IWSSIP58668.2023.10180296 | - |
dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação | por |
dc.subject.fos | Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | por |
dc.date.embargo | 2025-07-17 | - |
iscte.subject.ods | Indústria, inovação e infraestruturas | por |
iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-97040 | - |
Aparece nas coleções: | CIS-CRI - Comunicações a conferências internacionais ISTAR-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
Ficheiro | Tamanho | Formato | |
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conferenceobject_97040.pdf Restricted Access | 17,76 MB | Adobe PDF | Ver/Abrir Request a copy |
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