HUMAN ACTIVITY DETECTION SYSTEM
International Journal For Innovative Engineering and Management Research · 2022
The purpose of this project is to develop a model that would take the image input from different sources and detect actions that are being performed in them by the people also commonly referred to as Human actions recognition. The project starts by analyzing the procedures and models that already exist to perform this activity along with the assessment of their advantages and disadvantages respectively. There were many approaches to build this project that mainly used sensors and various modelling procedures such as Convolutional Neural Networks (CNN), Recurrent Neural Networks(RNN), Deep Neural Networks(DNN) and few Image Processing techniques. The goal is to come up with a model that is able to detect a selection of activities on which the model was trained during the development phase. The designed model helps to overcome the disadvantage of the previously built models that relied on the use of sensors. With the elimination of sensors, we eliminate the cost associated with respect to the sensors and the errors that can be caused due to the use of sensors. The vision-based HAR(human activity recognition) has produced fruitful findings with the advantage of high optical sensor resolution and the rapidly evolving computer vision techniques.