Multiple object tracking using RNNs
Tracking multiple objects simultaneously from a single camera is popular in surveillance systems. The standard methodology to address the problem is decomposing it in the object appearance modeling, object detection/tracking and data association. The majority of the related work focuses on improving
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2017 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/118345 |
| Acesso em linha: | https://hdl.handle.net/2117/118345 |
| Access Level: | acceso abierto |
| Palavra-chave: | Artificial intelligence Neural networks (Computer science) RNN MOT Tracking Intel·ligència artificial Xarxes neuronals (Informàtica) Àrees temàtiques de la UPC::Informàtica |
| Resumo: | Tracking multiple objects simultaneously from a single camera is popular in surveillance systems. The standard methodology to address the problem is decomposing it in the object appearance modeling, object detection/tracking and data association. The majority of the related work focuses on improving |
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