Human motion tracking with kinect sensors
Deep learning in the field of object detection has been the upcoming topic of machine learning in the recent years. Resulting in the development of various deep learning frameworks and models to improve on the accuracy of object detection in different scenarios and application. In this report, the...
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sg-ntu-dr.10356-782992023-07-07T17:33:35Z Human motion tracking with kinect sensors Teo, Shawn Meng yew Chau Lap Pui School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Deep learning in the field of object detection has been the upcoming topic of machine learning in the recent years. Resulting in the development of various deep learning frameworks and models to improve on the accuracy of object detection in different scenarios and application. In this report, the author will be explaining the concept of computer vision and the increase in demand of computer vision and machine learning in multiple industries. Elaborating on the theory, limitations applications of deep learning methods in the area of computer vision. This report provides a comprehensive study on a deep learning method that has been applied to a real-world scenario. The project is focused on identifying driver distraction. The author will demonstrate the process of gathering examples of driver distraction using Microsoft’s Kinect V2 to capture the actions. The author will then elaborate on the design of python scripts used to create the Convolutional Neural Network and the necessary processes that are needed to obtain a well-trained model. Bachelor of Engineering (Electrical and Electronic Engineering) 2019-06-17T03:03:32Z 2019-06-17T03:03:32Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78299 en Nanyang Technological University 68 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Teo, Shawn Meng yew Human motion tracking with kinect sensors |
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Deep learning in the field of object detection has been the upcoming topic of machine learning in the recent years. Resulting in the development of various deep learning frameworks and models to improve on the accuracy of object detection in different scenarios and application.
In this report, the author will be explaining the concept of computer vision and the increase in demand of computer vision and machine learning in multiple industries. Elaborating on the theory, limitations applications of deep learning methods in the area of computer vision.
This report provides a comprehensive study on a deep learning method that has been applied to a real-world scenario. The project is focused on identifying driver distraction. The author will demonstrate the process of gathering examples of driver distraction using Microsoft’s Kinect V2 to capture the actions. The author will then elaborate on the design of python scripts used to create the Convolutional Neural Network and the necessary processes that are needed to obtain a well-trained model. |
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Chau Lap Pui |
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Chau Lap Pui Teo, Shawn Meng yew |
format |
Final Year Project |
author |
Teo, Shawn Meng yew |
author_sort |
Teo, Shawn Meng yew |
title |
Human motion tracking with kinect sensors |
title_short |
Human motion tracking with kinect sensors |
title_full |
Human motion tracking with kinect sensors |
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Human motion tracking with kinect sensors |
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Human motion tracking with kinect sensors |
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human motion tracking with kinect sensors |
publishDate |
2019 |
url |
http://hdl.handle.net/10356/78299 |
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1772826968867209216 |