The Application of Genetic Algorithm in Motion Detection for Data Storage Optimization

Abstract

Abstract-The study focuses on detecting motion and capable of emitting insignificant parts of video from the captured frames from IP Camera and enhancing available data storage. This study embarks a system that is capable of minimizing the video in terms of eliminating frames which can't be used or are any of value to maximize the data storage available. Using the experimental method of research, the researchers evaluated the system based on the result of the experiments with regards to the scope and limitation of the problem and they assessed the accuracy of the system as highly acceptable. Implementing genetic algorithm helps the system to accurately detect motion and therefore optimize the data storage.

Storage Optimization using Adaptive Thresholding Motion Detection

“…Multimedia mining is a subfield of data-mining that addresses the issues of extracting information such as audio, text, links, images, or digital writing from multimedia files. Many researchers [7][8][9][10][11][12] worked on video mining, motion detection in CCTV cameras, and crime rate reduction. The importance of CCTV cameras and their placement was discussed in [7], concluding that although placing cameras in both random and expert-suggested sites reduced crime rates, the latter had more impact on crime rate reduction.…”

“…This method's drawbacks were the need for an external sensor for motion detection and the numerous emails in case of continuous motion. A genetic algorithm was utilized for motion detection in [12] to reduce surveillance data storage. The use of genetic algorithms for motion detection resulted in increased complexity and slow frame processing.…”