Abstract:The encounter between deep learning and big data technology has prompted face recognition technology to achieve a high level of accuracy. However, in actual application scenarios, especially in complex background, moving and natural face recognition, it has not yet achieved people’s satisfactory. Aiming at the problem of face recognition in attendance system, we propose using recursive minimum window algorithm to optimize the design of the face tracking algorithm in the M:N multi-face recognition scenario, and using multi angle sampling to improve the recognition accuracy and robustness. The proposed method is implemented and verified in the face attendance system. Achievement of multi-person synchronization within 3 seconds is achieved, and the user experience has been significantly improved.