CVMay 8, 2014

Implementation And Performance Evaluation Of Background Subtraction Algorithms

arXiv:1405.1815v132 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental review that helps designers choose suitable background subtraction methods for specific applications.

The study evaluated three background subtraction algorithms, ranging from basic to state-of-the-art, based on speed, memory, and accuracy to guide method selection for applications like real-time challenges including rain and varying light.

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.

Foundations

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