A system for detecting a pedestrian at a crosswalk and preventing an accident on the basis of artificial intelligence, the system comprising: a camera device installed on a mast arm installed at the top of a traffic light pole installed at a crosswalk to capture pedestrians and the vicinity of the crosswalk; a pedestrian detection module for detecting a pedestrian in an image captured by the camera device through a pre-installed image analysis solution; a color detection module for detecting a current blinking color of a traffic light consisting of a pedestrian traffic light and a driving traffic light; and a warning signal output module for outputting an unauthorized crossing warning message to the pedestrian waiting at the crosswalk according to a detection result of the color detection module and a detection result of the pedestrian detection module.

A system for detecting a pedestrian at a crosswalk and preventing an accident on the basis of artificial intelligence, the system comprising: a camera device installed on a mast arm installed at the top of a traffic light pole installed at a crosswalk to capture pedestrians and the vicinity of the crosswalk; a pedestrian detection module for detecting a pedestrian in an image captured by the camera device through a pre-installed image analysis solution; a color detection module for detecting a current blinking color of a traffic light consisting of a pedestrian traffic light and a driving traffic light; and a warning signal output module for outputting an unauthorized crossing warning message to the pedestrian waiting at the crosswalk according to a detection result of the color detection module and a detection result of the pedestrian detection module.

A face authentication apparatus (50) includes an image generation unit (102) that generates a first image by capturing an image of a person, a control unit (104) that, when the first image does not satisfy a criterion for face collation, controls lighting and causes the image generation unit (102) to generate a second image by capturing an image of the person again, and a face authentication unit (52) that executes face authentication by using the second image.

A face authentication apparatus (50) includes an image generation unit (102) that generates a first image by capturing an image of a person, a control unit (104) that, when the first image does not satisfy a criterion for face collation, controls lighting and causes the image generation unit (102) to generate a second image by capturing an image of the person again, and a face authentication unit (52) that executes face authentication by using the second image.

A learning data generation device that can generate learning data suitable for learning of an identification model. The learning data generation device has a function of cutting out part of first image data as second image data, a function of generating a two-dimensional graphic corresponding to the area of the second image data and representing a pseudo defect, a function of generating third image data by combining the second image data and the two-dimensional graphic, and a function of assigning a label corresponding to the two-dimensional graphic to the third image data. By using the third image data for learning of the identification model, a highly accurate identification model can be generated.

A learning data generation device that can generate learning data suitable for learning of an identification model. The learning data generation device has a function of cutting out part of first image data as second image data, a function of generating a two-dimensional graphic corresponding to the area of the second image data and representing a pseudo defect, a function of generating third image data by combining the second image data and the two-dimensional graphic, and a function of assigning a label corresponding to the two-dimensional graphic to the third image data. By using the third image data for learning of the identification model, a highly accurate identification model can be generated.

Object detection is performed for an image acquired by imaging using an array sensor in which a plurality of imaging elements are arranged one-dimensionally or two-dimensionally, some of the imaging elements are configured as color-filter-disposed pixels in which a color filter is disposed in an incident optical path, and color information acquisition points are formed by the color-filter-disposed pixels. Then, coloring processing in a pixel range of a detected object is performed by referring to color information acquired at the color information acquisition points corresponding to the inside of the pixel range of the detected object.

Object detection is performed for an image acquired by imaging using an array sensor in which a plurality of imaging elements are arranged one-dimensionally or two-dimensionally, some of the imaging elements are configured as color-filter-disposed pixels in which a color filter is disposed in an incident optical path, and color information acquisition points are formed by the color-filter-disposed pixels. Then, coloring processing in a pixel range of a detected object is performed by referring to color information acquired at the color information acquisition points corresponding to the inside of the pixel range of the detected object.

A handwash monitoring system includes: an imaging device; and a processor. The processor detects a first candidate abnormality existing in a hand of a user from a first image captured by the imaging device before handwashing, and detects a second candidate abnormality existing in the hand of the user from a second image captured by the imaging device after the handwashing. The processor determines a type of an abnormality on the hand of the user based on a difference between a shape of the first candidate abnormality and a shape of the second candidate abnormality wherein the first candidate abnormality and the second candidate abnormality are detected from an identical region.

A handwash monitoring system includes: an imaging device; and a processor. The processor detects a first candidate abnormality existing in a hand of a user from a first image captured by the imaging device before handwashing, and detects a second candidate abnormality existing in the hand of the user from a second image captured by the imaging device after the handwashing. The processor determines a type of an abnormality on the hand of the user based on a difference between a shape of the first candidate abnormality and a shape of the second candidate abnormality wherein the first candidate abnormality and the second candidate abnormality are detected from an identical region.