Siu, Wan ChiWan ChiSiuCheng, YihaoYihaoChengChan, Anthony Hing-HungAnthony Hing-HungChanWang, L.-W.2025-02-262025-02-262024https://repository.sfu.edu.hk/handle/sfu/4536Student recognition in smart classrooms is challenging due to low resolution, occlusions, and various face orientations. We propose a video-based approach for robust face recognition. It firstly collects a continuous sequence of face images through inter-frame analysis. Then, it aggregates face features, via statistical elimination of outliers. We introduce a new consistency loss to address varying face resolutions, enabling the learning of scale-robust features. Experimental results demonstrate that our proposed approach improves recognition performance under various conditions compared to previous methods. In our experiments, it achieved the highest recognition accuracy (83.57%) for 8×8 resolution cases.enconference proceedings10.1109/ISCAS58744.2024.10558195