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Passenger Counting With Face Detection

Passenger counting exhibits a wide variety of applications in the context of smart cities. Such applications range from retail analytics, queue management and space utilizations. Driven by the success of machine learning, this study aims to develop a real-time passenger counting system. Different fr...

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Bibliographic Details
Main Author: Teoh, Han Wei
Format: Final Year Project / Dissertation / Thesis
Published: 2020
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://eprints.utar.edu.my/4221/1/1505028_FYP_report_%2D_HAN_WEI_TEOH.pdf
http://eprints.utar.edu.my/4221/
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id my-utar-eprints.4221
record_format eprints
spelling my-utar-eprints.42212021-08-11T13:19:21Z Passenger Counting With Face Detection Teoh, Han Wei TJ Mechanical engineering and machinery Passenger counting exhibits a wide variety of applications in the context of smart cities. Such applications range from retail analytics, queue management and space utilizations. Driven by the success of machine learning, this study aims to develop a real-time passenger counting system. Different from existing works, the designed solution is deployed on a resource limited Intel UP Squared (UP2 ) Board, inference of which is handled by an accelerator called Intel Movidius Neural Compute Stick 2 (NCS2). MobileNet-single shot detector (SSD) is chosen as the object detector model since it belongs to a class of efficient models that can execute on mobile and embedded systems. While running detections across every video frames, centroid tracking algorithm tracks every unique person in video streams, where Kalman filter is further applied to reduce the noise. The outcome can be visualized on different type of devices for further analysis through a central cloud server. The performance of the passenger counting system is evaluated in terms of accuracy and frame per second (FPS). Furthermore, the feasibility of the solution is demonstrated in several showcases. 2020 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4221/1/1505028_FYP_report_%2D_HAN_WEI_TEOH.pdf Teoh, Han Wei (2020) Passenger Counting With Face Detection. Final Year Project, UTAR. http://eprints.utar.edu.my/4221/
institution Universiti Tunku Abdul Rahman
building UTAR Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
url_provider http://eprints.utar.edu.my
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Teoh, Han Wei
Passenger Counting With Face Detection
description Passenger counting exhibits a wide variety of applications in the context of smart cities. Such applications range from retail analytics, queue management and space utilizations. Driven by the success of machine learning, this study aims to develop a real-time passenger counting system. Different from existing works, the designed solution is deployed on a resource limited Intel UP Squared (UP2 ) Board, inference of which is handled by an accelerator called Intel Movidius Neural Compute Stick 2 (NCS2). MobileNet-single shot detector (SSD) is chosen as the object detector model since it belongs to a class of efficient models that can execute on mobile and embedded systems. While running detections across every video frames, centroid tracking algorithm tracks every unique person in video streams, where Kalman filter is further applied to reduce the noise. The outcome can be visualized on different type of devices for further analysis through a central cloud server. The performance of the passenger counting system is evaluated in terms of accuracy and frame per second (FPS). Furthermore, the feasibility of the solution is demonstrated in several showcases.
format Final Year Project / Dissertation / Thesis
author Teoh, Han Wei
author_facet Teoh, Han Wei
author_sort Teoh, Han Wei
title Passenger Counting With Face Detection
title_short Passenger Counting With Face Detection
title_full Passenger Counting With Face Detection
title_fullStr Passenger Counting With Face Detection
title_full_unstemmed Passenger Counting With Face Detection
title_sort passenger counting with face detection
publishDate 2020
url http://eprints.utar.edu.my/4221/1/1505028_FYP_report_%2D_HAN_WEI_TEOH.pdf
http://eprints.utar.edu.my/4221/
_version_ 1709672666940571648
score 13.211869

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