Background subtraction is an advanced method used for video monitoring and is commonly used for indexing of moveable objects. Over the years, several algorithms have been implemented and the implementation of algorithms on the embedded platform can be difficult because the embedded platform has minimal computing resources. The purpose of this study is to conduct a comparative review of background subtraction algorithms available on the embedded platform: Raspberry Pi. The algorithms are compared using a real video dataset based on segmentation accuracy (precision, recall, and f-measure) and hardware efficiency (CPU utilization and time consumption).
