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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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 |
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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 |
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