Ndyamuhakyi, OsbartNabukenya, Eva2024-07-172024-07-172024Ndyamuhakyi, Osbart & Nabukenya, Eva (2024). Student Attendance System by Face Detection Using the Dlib Face Detector Model. Kabale: Kabale University.http://hdl.handle.net/20.500.12493/2262This report shows how we developed a prototype of a student attendance system by face detection using the dlib face detector and Face Recognition model to build a system that detects and recognizes the frontal faces of students in a lecture room and online lectures. “A face was defined as the front part of a person’s head from the forehead to the chin, or the corresponding part of an animal”. In human interactions, the face is defined as the most important factor as it contains important information about a person or individual. All humans can recognize individuals from their faces. This report shows a developed prototype of a system that facilitates attendance taking by lectures for Kabale University in lecture rooms and online lectures by detecting the faces of students from a video taken in a lecture room/ online lecture. In recent years, research has been carried out and face recognition and detection systems have been developed. Some of these are used on social media platforms, banking apps, and government offices e.g. the Metropolitan Police, Facebook, etc.enAttribution-NonCommercial-NoDerivs 3.0 United Stateshttp://creativecommons.org/licenses/by-nc-nd/3.0/us/Student Attendance SystemFace DetectionDlib Face Detector ModelThesis