A Robust Framework for Automatic Crowd Video Summarization Using Deep Learning Methodology

Abstract

The increasing popularity of surveillance systems has resulted in a massive impact of newlinesurveillance footage, which requires manual analysis to extract meaningful insights. newlineThe proposed framework aims to address this challenge by automatically generating a newlineconcise summary of the crowd video. The framework utilizes deep learning methods to newlineextract relevant features and apply clustering algorithms to group similar events. newlineThe proposed research work includes three different approaches to video analysis and newlinemanagement. The first research proposes a novel approach for automatic video newlinesummarization using crowded videos. The proposed framework combines Bayesian newlinefuzzy clustering and deep learning techniques to extract the most important events from newlinethe video while minimizing information loss. The system utilizes deep learning to newlineextract salient features and fuzzy clustering to group similar events. newline