Implementation And Performance Evaluation Of Background Subtraction Algorithms

TL;DR

This paper reviews and evaluates three background subtraction algorithms, comparing their speed, memory use, and accuracy to guide application-specific selection, including real-time challenges.

Contribution

It provides a comprehensive comparison of background subtraction techniques, highlighting their suitability for different real-world scenarios.

Findings

Algorithms vary in accuracy and computational complexity.

Some methods handle real-time challenges like weather and lighting.

Guidelines for selecting appropriate algorithms are provided.

Abstract

The study evaluates three background subtraction techniques. The techniques ranges from very basic algorithm to state of the art published techniques categorized based on speed, memory requirements and accuracy. Such a review can effectively guide the designer to select the most suitable method for a given application in a principled way. The algorithms used in the study ranges from varying levels of accuracy and computational complexity. Few of them can also deal with real time challenges like rain, snow, hails, swaying branches, objects overlapping, varying light intensity or slow moving objects.