Abstract
This paper shows a Novel Low Processing Time System focused on criminal activities detection based on real-time video analysis applied to Command and Control Citizen Security Centers. This system was applied to the detection and classification of criminal events in a real-time video surveillance subsystem in the Command and Control Citizen Security Center of the Colombian National Police. It was developed using a novel application of Deep Learning, specifically a Faster Region-Based Convolutional Network (R-CNN) for the detection of criminal activities treated as “objects” to be detected in real-time video. In order to maximize the system efficiency and reduce the processing time of each video frame, the pretrained CNN (Convolutional Neural Network) model AlexNet was used and the fine training was carried out with a dataset built for this project, formed by objects commonly used in criminal activities such as short firearms and bladed weapons. In addition, the system was trained for street theft detection. The system can generate alarms when detecting street theft, short firearms and bladed weapons, improving situational awareness and facilitating strategic decision making in the Command and Control Citizen Security Center of the Colombian National Police.
Highlights
Colombia is a country with approximately 49 million inhabitants, 77% of which live in cities [1], and as in many Latin American countries, some Colombian cities suffer from insecurity
Several recent applications of Faster Region-Based Convolutional Network (R-CNN) have shown great performance as object detector [48,49,50,51,52], this work demonstrated that applying object detection techniques based on Deep Learning like Faster R-CNN in actions detection could be an alternative to action recognition based on analysis of trajectories or movements and could be applied more in highly mobile video environments, such as military operations, transportation, citizen security, and national security to name only a few, human supervision is always required, because after a while, the quantity of False Negatives and False Positive could drastically reduce the system effectiveness, which is very serious in safety applications
During the development of the Video Detection and Classification System (VD&CS), it has been proven that it is possible to improve situational awareness in the Command and Control Citizen Security Center of the Colombian National Police, triggering alarms of criminal events captured by the video surveillance system
Summary
Julio Suarez-Paez 1, * , Mayra Salcedo-Gonzalez 1 , Alfonso Climente 1 , Manuel Esteve 1 , Jon Ander Gómez 2 , Carlos Enrique Palau 1 and Israel Pérez-Llopis 1. Pattern Recognition and Human Language Technologies, Universitat Politècnica de València, Camino de. Received: 16 October 2019; Accepted: 20 November 2019; Published: 24 November 2019
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