A survey on human detection surveillance systems for Raspberry Pi

Building reliable surveillance systems is critical for security and safety. A core component of any surveillance system is the human detection model. With the recent advances in the hardware and embedded devices, it becomes possible to make a real-time human detection system with low cost. This pape...

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Bibliographic Details
Published in:Image and vision computing Vol. 85; pp. 1 - 13
Main Authors: Farouk Khalifa, Ali, Badr, Eman, Elmahdy, Hesham N.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.05.2019
Subjects:
Human detection
Machine learning
Raspberry Pi
Human detection
Raspberry Pi
Machine learning
ISSN:0262-8856, 1872-8138
Online Access:Get full text
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Summary:Building reliable surveillance systems is critical for security and safety. A core component of any surveillance system is the human detection model. With the recent advances in the hardware and embedded devices, it becomes possible to make a real-time human detection system with low cost. This paper surveys different systems and techniques that have been deployed on embedded devices such as Raspberry Pi. The characteristics of datasets, feature extraction techniques, and machine learning models are covered. A unified dataset is utilized to compare different systems with respect to accuracy and performance time. New enhancements are suggested, and future research directions are highlighted.
ISSN:0262-8856
1872-8138
DOI:10.1016/j.imavis.2019.02.010