Smart Surveillance and Tracking System using Resnet and Tesseract-OCR

Abstract

In recent times the field of computer vision and deep learning has seen many advancements that have helped in efficient and accurate face and object detection, resulting in many security and surveillance applications. Furthermore, with the increase in localized cameras monitoring every human action, every vehicle tracked it only seemed logical to use these camera's video feeds more efficiently and smartly. Present security systems include manual surveillance or a single smart camera setup. In this paper, we propose a smart multi-camera system using a Resnet-34 model for face recognition and Tesseract-based Optical Character Recognition for vehicle number plate recognition. The individuals and vehicles captured in the multiple cameras are traced out on a map which will graphically show when and where they were detected. This security and surveillance system will be beneficial in large organizations such as offices, banks, shopping malls, residential areas, etc.