An Analysis of Background Subtraction on Embedded Platform Based on Synthetic Dataset

Background subtraction is a preliminary technique used for video surveillance and a widely used approach for indexing moving objects. Arange of algorithms have been introduced over the years, and it might be hard to implement the algorithms on the embedded platform because the embedded platform come...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-02, Vol.1755 (1), p.12042
Main Authors: Iszaidy, I., Ngadiran, R., Ahmad, R.B., Ramli, N., Jais, M.I., Vijayasarveswari, V.
Format: Article
Language:English
Subjects:
Algorithms
Datasets
Physics
Segmentation
Subtraction
Synthetic data
Weather
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Summary:Background subtraction is a preliminary technique used for video surveillance and a widely used approach for indexing moving objects. Arange of algorithms have been introduced over the years, and it might be hard to implement the algorithms on the embedded platform because the embedded platform comes up with limited processing power. The goal of this study is to provide a comparative analysis of available background subtraction algorithms on the embedded platform: - Raspberry Pi. The algorithms are compared based on the segmentation quality (precision, recall, and f-measure) and hardware performance(CPU usage and time consumption) using a synthetic video from BMC Dataset with different challenges like normal weather, sunny, cloudy, foggy and windy weather.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1755/1/012042