Skeleton recognition method, non-transitory computer-readable recording medium, and gymnastics scoring assist system

A non-transitory computer-readable recording medium having stored therein a skeleton recognition program that causes a computer to execute a process comprising:

• extracting a plurality of first features presenting features of two-dimensional joint positions of a subject, based on two-dimensional input images that are input from a plurality of cameras that capture images of a subject;
• generating, based on the first features, second feature group information containing a plurality of second features corresponding to a given number of joints of the subject, respectively;
• sensing an abnormal second feature from the second feature group information;
• and
• recognizing a 3D skeleton based on a result of integrating the second features that remain after removal of the abnormal second feature from the second feature group information,
• wherein the second feature is coordinates and heatmap information in which likelihood of presence of a given joint is associated with the coordinates, and
• the sensing senses an abnormal feature based on a difference between the heatmap information and information of Gaussian distribution of likelihood that is specified previously.

A gymnastics scoring assist system including a plurality of cameras that capture images of a subject and a skeleton recognition apparatus comprising:

• a processor configured to:
• acquire two-dimensional input images that are input from the cameras;
• extract a plurality of first features presenting features of two-dimensional joint positions of the subject based on the input images
• generate, based on the first features, second feature group information containing a plurality of second features corresponding to a given number of joints of the subject, respectively;
• sense an abnormal second feature from the second feature group information;
• and
• recognize a 3D skeleton based on a result of synthesizing second features that remain after removal of the abnormal second feature from the second feature group information,
• wherein the second feature is coordinates and heatmap information in which likelihood of presence of a given joint is associated with the coordinates and the processor is further configured to sense an abnormal feature based on a difference between the heatmap information and information of Gaussian distribution of likelihood that is specified previously.