Human and Object Detection using Machine Learning Algorithm

Films with abandoned objects may be identified and traced using this paper’s technique. Especially in high-traffic locations like railway stations and airports, unattended baggage poses a severe security risk. By using the power of deep learning, people and their belongings may be accurately recognized. Each photograph is accompanied by a training video that comprises more than 18,000 people and their baggage (such as backpacks and purses). The YOLOv3 model is used, which has a real-time accuracy of 98 percent. Determine who owns something and if it has been abandoned. People and their luggage may be studied using an approach that takes into account their location and travel patterns. 65.66% of the time, abandoned properties and their owners are correctly identified 65.10% of the time, ownership is also correctly identified.