The Final Year Project (FYP) is a crucial component of the Bachelor of Computer Science degree. It involves working in a team of two students over the final two semesters of university. This project spans the final year of studies and includes several key stages. You defend your project proposal at the beginning of the seventh semester, followed by an evaluation known as FYP-I at the end of the same semester. In the final semester, there is a mid-evaluation, followed by a final evaluation. The project is then showcased at the FYP Open House, where it is presented to both internal and external juries. For detailed information about the FYP process at NUCES-FAST, visit their FYP page.
This was a research based project on Human Activity Recognition aimed to discover a more precise and efficient method of identifying human activities in videos, utilizing Deep Learning Models, particularly within the domain of Computer Vision.
Automated systems (particularly surveillance systems) are in demand for the classification of various human actions as the number of cameras grows day by day. Furthermore, human action recognition (HAR) has emerged as one of the most appealing study subjects across a wide range of computer vision applications. The precise detection of human activity on an uncertain basis, on the other hand, remains a mystery. There has been limited study on human action recognition processes in real situations, which drives us to pursue research in this application space. In this paper, we examined several approaches, including CNN+LSTM, Inception-V3+CNN, MobileNet, and Inception-V3. Experiments are carried out on the UCF-101 dataset to demonstrate the effectiveness of new models.
To read more about our research, Click HERE