Application of Hill Climbing Algorithm as Data Mining Technique for Surveillance of Real Time Video Streams

Abstract

Data mining is the application of statistical techniques and programmatic algorithms to discover previously unnoticed relationships within the data. Video surveillance has long been in use to monitor security sensitive areas such as banks, department stores, highways, crowded public places and borders. The advance in computing power, availability of large-capacity storage devices and high speed network infrastructure paved the way for cheaper, multi sensor video surveillance systems. The ultimate goal of the present generation surveillance systems is to allow video data to be used for on-line alarm generation to assist human operators and for offline inspection effectively. Moving object detection is the basic step for further analysis of video.