CRIME VIDEO ANALYSIS AND SUMMARIZATION DASHBOARD

Abstract: This paper presents a Crime Video Analysis and Summarization Dashboard that leverages Deep Learning, Computer Vision, and Natural Language Processing (NLP) to automate the detection, classification, and summarization of criminal activities captured in surveillance footage. The system employs Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for real-time anomaly detection and activity recognition in video streams. An intelligent summarization engine condenses lengthy footage into concise, timestamped crime event reports, reducing manual review time significantly. The dashboard provides law enforcement agencies with an intuitive interface to monitor, query, and export summarized incident reports. The proposed system improves investigation efficiency, enhances situational awareness, and supports smarter, data-driven public safety management.

Keywords: Crime Detection, Video Summarization, Deep Learning, CNN, LSTM, Surveillance, Anomaly Detection, NLP, Public Safety, Smart Dashboard