Deep Learning Enhanced Human Activity Recognition and Behaviour Analysis with OpenCV Integration

This innovative system transforms behavioral analysis and human activity detection. With the increase in surveillance and wearable technology, there’s a demand for reliable systems that identify human activities in real-time and interpret behavioral patterns—this system meets that need. It leverages deep neural networks to detect various activities through live camera feeds or video streams and preprocesses raw image data using OpenCV to enhance image quality and extract features. The trained models accurately recognize actions like jogging, walking, sitting, or standing, making it valuable for applications in surveillance, healthcare, and smart environments. Beyond mere activity recognition, it identifies abnormal behavior, predicts future actions, and assesses behavioral patterns over time. The tool’s user-friendly design further simplifies behavior analysis by presenting results with visual insights, marking a significant advancement in human activity recognition technology.