Security system for facility access control

A computer-implemented method for facility access control, the method comprising:

• capturing, by a camera, an input image of a subject attempting to enter or exit a restricted facility;
• storing, in a memory, a deep learning model configured to perform multi-task learning for a pair of tasks including a liveness detection task and a face recognition task;
• and
• applying, by a processor, the deep learning model to the input image to recognize an identity of the subject in the input image regarding being authorized for access to the facility and a liveness of the subject, and wherein the liveness detection task is configured to evaluate a plurality of different distracter modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task.

A computer program product for facility access control, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising:

• capturing, by a camera, an input image of a subject attempting to enter or exit a restricted facility;
• storing, in a memory, a deep learning model configured to perform multi-task learning for a pair of tasks including a liveness detection task and a face recognition task;
• and
• applying, by a processor, the deep learning model to the input image to recognize an identity of the subject in the input image regarding being authorized for access to the facility and a liveness of the subject, and wherein the liveness detection task is configured to evaluate a plurality of different distracter modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task.