Advanced Home Surveillance Using openCV and ML

• Published in: 2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS) pp. 1 - 4
• Main Authors: Kumar, D. Sathish, Arul, Shivan, Vignesh, J
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14-12-2023
• Subjects: Cameras; Face recognition; Machine learning; Real-time systems; Security; Streaming media; Video surveillance
• DOI: 10.1109/ICCEBS58601.2023.10448826

Security is a major worry in today's world. Due to multiple detailed obligations, the demands of our busy life frequently led to homes being left neglected. To solve this worry, the majority of people have resorted to Closed Circuit Television (CCTV) cameras to protect their homes while they are abroad. In the context of smart cities, surveillance camera video plays a critical role in crime prevention and investigation. However, it is worth mentioning that traditional video surveillance, which primarily records without undertaking object analysis, is seen as less effective in the face of developing security issues. So, we use openCV for optimised image processing. We'll have an initial image and then capture an image if any motion is detected and compare structural similarity on both the images to detect any missing object. Another major feature of this project is face-recognition which is done using LBPH Face-Identification method. Using Machine Learning, first we will train the model with the dataset then we will detect the presence of face in frames. After that we make predictions by using the trained model to accurately identify the person.