Human Based Surveillance Video Summarization

Abstract

In this work, a new human based video summarization system designed and implemented which receives video frames from surveillance cameras.. For analyzing the human centric videos, optical flow used as motion descriptor and histogram of gradients used as feature extractor. During the video motion information of object has been made continuous by adding time information to histograms with gradient information. Template matching method is applied on the continuous gradient information to find beginnings of movement patterns and beginnings of repetition the movement patterns. Summarization is built up on the validation of these extracted patterns with a correlation based search-through subsystem.