In-House Facial Data Collection for Face Recognition Accuracy: Dataset Accuracy Analysis
Taufiq Maulana Firdaus, Tien Fabrianti Kusumasari, Sinung Suakanto, Oktariani Nurul Pratiwi · 2023
The face recognition system is a field of research that can help identify a person for either a security system or a search system because faces are distinctive from each person. The development of a human face recognition model requires several main components, such as scale, light, and expression. This study aims to collect accurate samples of Indonesian faces for face detection algorithms. Determining these facial features is challenging to identify Indonesian faces because Indonesia consists of various tribes. In contrast, the classification of tribes in Indonesia consists of Malay and non-Malay tribes. Therefore, this study uses an in-house dataset of Indonesian people's faces which will be tested using the FaceNet algorithm. The results of this study indicate that high accuracy is obtained even when using simple devices. The benefit of this study is that using the in-house method used by researchers can improve the accuracy of test results even though using an in-house dataset.