Abstract: A facility access control system and corresponding method are provided. The facility access control system includes a camera configured to capture an input image of a subject attempting to enter or exit a restricted facility. The facility access control system further includes a memory storing 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. The facility access control system also includes a processor configured to apply 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. 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.

Abstract: A smuggling detection system and corresponding method are provided. The smuggling detection system includes a camera configured to capture an input image of a subject purported to be a baby. The smuggling detection system further includes a memory storing a deep learning model configured to perform a baby detection task for a smuggling detection application. The smuggling detection system also includes a processor configured to apply the deep learning model to the input image to provide a baby detection result of either a presence or an absence of an actual baby in relation to the subject purported to be the baby. The baby detection task is configured to evaluate one or more different distractor modalities corresponding to one or more different physical spoofing materials to prevent baby spoofing for the baby detection task.

Abstract: A machine access control system and corresponding method are provided. The machine access control system includes a camera configured to capture an input image of a subject purported to be a person associated with operating a particular workplace machine. The machine access control system further includes a memory storing 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. The machine access control system also includes a processor configured to apply the deep learning model to the input image to recognize an identity of the subject in the input image regarding being authorized to use the particular workplace machine and a liveness of the subject. 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.

Abstract: A baby detection system and corresponding method are provided. The baby detection system includes a camera configured to capture an input image of a subject purported to be a baby and presented at an electronic-gate system. The baby detection system further includes a memory storing a deep learning model configured to perform a baby detection task for an electronic-gate application corresponding to the electronic-gate system. The baby detection system also includes a processor configured to apply the deep learning model to the input image to provide a baby detection result of either a presence or an absence of an actual baby in relation to the subject purported to be the baby. The baby detection task is configured to evaluate one or more different distractor modalities corresponding to one or more different physical spoofing materials to prevent baby spoofing for the baby detection task.

Abstract: A time difference measurement system includes: a first face detection unit for detecting face areas from images photographed by first camera and that slices them as face images; a first face feature extraction unit for extracting first face feature amounts from the face images, and a memory that stores the first face feature amounts in association with shooting time instants. The system includes, for a second camera, an analogous second face detection unit, a second overlap deletion unit and a second face feature extraction unit. The system includes: a face collation unit for collating the second face feature amounts with the first face values; and a time difference calculation unit for calculating time difference between the first and second shooting time instants. The system further includes at least one of first and second overlap deletion units for comparing a plurality of face images sliced from different frames.