Automated Human Tracing Using Gait and Face Using Artificial Neural Network in Surveillance System
Lecture Notes on Data Engineering and Communications Technologies
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
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