Cargando…

XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera

A low-cost and power-efficient video surveillance system, named XDMOM, is developed for real-time moving object detection outdoors or in the wild. The novel system comprises four parts: imaging subsystem, video processing unit, power supply, and alarm device. The imaging subsystem, which consists of...

Descripción completa

Detalles Bibliográficos
Autores principales: Shi, Baoquan, Gu, Weichen, Sun, Xudong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144562/
https://www.ncbi.nlm.nih.gov/pubmed/35632314
http://dx.doi.org/10.3390/s22103905
_version_ 1784716078455193600
author Shi, Baoquan
Gu, Weichen
Sun, Xudong
author_facet Shi, Baoquan
Gu, Weichen
Sun, Xudong
author_sort Shi, Baoquan
collection PubMed
description A low-cost and power-efficient video surveillance system, named XDMOM, is developed for real-time moving object detection outdoors or in the wild. The novel system comprises four parts: imaging subsystem, video processing unit, power supply, and alarm device. The imaging subsystem, which consists of a dual-spectrum camera and rotary platform, can realize 360-degree and all-day monitoring. The video processing unit uses a power-efficient NVIDIA GeForce GT1030 chip as the processor, which ensures the power consumption of the whole system maintains a low level of 60~70 W during work. A portable lithium battery is employed to supply power so that the novel system can be used anywhere. The work principle is also studied in detail. Once videos are recorded, the single-stage neural network YOLOv4-tiny is employed to detect objects in a single frame, and an adaptive weighted moving pipeline filter is developed to remove pseudo-targets in the time domain, thereby reducing false alarms. Experimental results show that the overall correct alarm rate of the novel system could reach 85.17% in the daytime and 81.79% at night when humans are monitored in real outdoor environments. The good performance of the novel system is demonstrated by comparison with state-of-the-art video surveillance systems.
format Online
Article
Text
id pubmed-9144562
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-91445622022-05-29 XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera Shi, Baoquan Gu, Weichen Sun, Xudong Sensors (Basel) Article A low-cost and power-efficient video surveillance system, named XDMOM, is developed for real-time moving object detection outdoors or in the wild. The novel system comprises four parts: imaging subsystem, video processing unit, power supply, and alarm device. The imaging subsystem, which consists of a dual-spectrum camera and rotary platform, can realize 360-degree and all-day monitoring. The video processing unit uses a power-efficient NVIDIA GeForce GT1030 chip as the processor, which ensures the power consumption of the whole system maintains a low level of 60~70 W during work. A portable lithium battery is employed to supply power so that the novel system can be used anywhere. The work principle is also studied in detail. Once videos are recorded, the single-stage neural network YOLOv4-tiny is employed to detect objects in a single frame, and an adaptive weighted moving pipeline filter is developed to remove pseudo-targets in the time domain, thereby reducing false alarms. Experimental results show that the overall correct alarm rate of the novel system could reach 85.17% in the daytime and 81.79% at night when humans are monitored in real outdoor environments. The good performance of the novel system is demonstrated by comparison with state-of-the-art video surveillance systems. MDPI 2022-05-21 /pmc/articles/PMC9144562/ /pubmed/35632314 http://dx.doi.org/10.3390/s22103905 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shi, Baoquan
Gu, Weichen
Sun, Xudong
XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera
title XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera
title_full XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera
title_fullStr XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera
title_full_unstemmed XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera
title_short XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera
title_sort xdmom: a real-time moving object detection system based on a dual-spectrum camera
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144562/
https://www.ncbi.nlm.nih.gov/pubmed/35632314
http://dx.doi.org/10.3390/s22103905
work_keys_str_mv AT shibaoquan xdmomarealtimemovingobjectdetectionsystembasedonadualspectrumcamera
AT guweichen xdmomarealtimemovingobjectdetectionsystembasedonadualspectrumcamera
AT sunxudong xdmomarealtimemovingobjectdetectionsystembasedonadualspectrumcamera