Camera system for traffic enforcement

A computer-implemented method for traffic enforcement, the method comprising:

• capturing, by a camera, an input image of one or more subjects in a motor vehicle;
• 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 on one or more subjects in a motor vehicle depicted in the input image;
• and
• applying, by a processor, the deep learning model to the input image to recognize an identity the one or more subjects in the motor vehicle and a liveness of the one or more subjects, and wherein the liveness detection task is configured to evaluate a plurality of different distractor modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task.

A computer program product for traffic enforcement, 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 one or more subjects in a motor vehicle;
• 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 on one or more subjects in a motor vehicle depicted in the input image;
• and
• applying, by a processor, the deep learning model to the input image to recognize an identity the one or more subjects in the motor vehicle and a liveness of the one or more subjects, and wherein the liveness detection task is configured to evaluate a plurality of different distractor modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task.