Human Activity Tracking System Using Pose Estimation Technique

Abstract

Abstract: When some incident / any dangerous activity happens in the area the CCTV takes photos & video pieces of evidence of what happened there, but there are only few such system that can capture evidence in real-time and process it to conduct further actions of an incident. It waits for the police to come and resolve the issue and what happens is when police come the evidence are vanished. The drawbacks are that when such an incident happens out of 10 people only 1 or 2 will try tocall the police or ambulance but this also takes a lot of time, no quick decisions are taken to resolve the issue until the police gets informed about it. Also, if the accident / suspicious activityhappens on road then that road routes get blocked in some cases, the system’s model should be accurate enough to observethe situation and by predictions should proceed with the decision-making to help police to resolve the issue smoothly and as early as possible. Our solution for such a problem is to develop a system that uses CCTV surveillance systems with an advanced technological model with which it can capture required evidence. Also, we had developed a system that can recognize gestures of a person to detect if he/she is beating someone in the Realtime footage with the help of CNN, Keras, YOLO, MediaPipe and TensorFlow libraries. Quick notifications are sent to alert the police control rooms. At Control room police will allot the nearby required FRVs clusters by sending notifications to them of incident happened in a particular area