Design of Real-Time Multiple Object Visual Detection and Tracking Systems
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http://hdl.handle.net/10347/26471
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Título: | Design of Real-Time Multiple Object Visual Detection and Tracking Systems |
Autor/a: | Fernández Sanjurjo, Mauro |
Dirección/Titoría: | Mucientes Molina, Manuel Brea Sánchez, Víctor Manuel |
Centro/Departamento: | Universidade de Santiago de Compostela. Escola de Doutoramento Internacional (EDIUS) Universidade de Santiago de Compostela. Programa de Doutoramento en Investigación en Tecnoloxías da Información |
Palabras chave: | multiple object tracking | visual tracking | edge computing | deep learning | convolutional neural networks (CNNs) | data association | computer vision | traffic monitoring | |
Data: | 2021 |
Resumo: | Multiple object detection and tracking is one of the main topics in computer vision. The task is to identify all the objects of interest in a frame of a video and to assign an unique ID to those instances that correspond to the same object while it appears in the scene. This is a fundamental task of many video analytics applications like traffic monitoring or video surveillance, which usually requires real-time processing speed and its execution on different hardware devices. In this PhD Thesis we address the topic of Real-Time Multiple Object Detection and Tracking Systems, combining state-of-the-art detectors, trackers and data association techniques. Particularly, we focus on the design of Real- Time Multiple Object Detection and Tracking systems for both server architectures and embedded devices, that are able to work with dozens of objects in real-time. |
URI: | http://hdl.handle.net/10347/26471 |
Dereitos: | Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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