Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/78299
Title: Human motion tracking with kinect sensors
Authors: Teo, Shawn Meng yew
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2019
Abstract: 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.
URI: http://hdl.handle.net/10356/78299
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP report U1620963L.pdf
  Restricted Access
Project Report4.78 MBAdobe PDFView/Open

Page view(s)

377
Updated on May 7, 2025

Download(s) 50

53
Updated on May 7, 2025

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.