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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| Format: | Master's thesis |
| Publication date: | 2017 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/118345 |
| Online Access: | https://hdl.handle.net/2117/118345 |
| Access Level: | Open access |
| Keyword: | Artificial intelligence Neural networks (Computer science) RNN MOT Tracking Intel·ligència artificial Xarxes neuronals (Informàtica) Àrees temàtiques de la UPC::Informàtica |
| Summary: | 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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