Automated Human Tracing Using Gait and Face Using Artificial Neural Network in Surveillance System
Publication Name
Lecture Notes on Data Engineering and Communications Technologies
Abstract
It is challenging to authenticate people utilizing a camera-based monitoring system. Sometimes face of humans is not clear, therefore we use both face and gait to recognize the correct human. This paper presents a model to search for human beings using a surveillance system. Nowadays we are using cameras in each corner. These cameras connect with the network and send data to a cloud storage mechanism. We collect both face and gait using a camera and after fusion (“face” + “gait”) find a score and match it with online stream data. Through this, we can search any human using breadth-first search algorithm in stream data. In this model, we use artificial neural network. Even in circumstances where individuals are unwilling to cooperate or are not informed, this system exhibits a high level of accuracy.
Open Access Status
This publication is not available as open access
Volume
175
First Page
277
Last Page
292