Method for identifying human poses in an image, computer system, and non-transitory computer-readable medium

A computer system, comprising:

• one or more processors;
• and
• memory having instructions stored thereon, which when executed by the one or more processors cause the processors to perform a method for identifying human poses in an image;
• wherein the method comprises;
• obtaining the image;
• encoding the image into a feature map;
• converting the feature map into a plurality of Truncated Part Displacement Field (TPDF) maps corresponding to a plurality of predefined part types, where:
• each TPDF map corresponds to a respective predefined part type, and the image comprises one or more body parts of the respective predefined part type;
• each TPDF map comprises an x-axis displacement map and a y-axis displacement map, and represents a plurality of vectors connecting each position on the image to a closest body part among the one or more body parts of the respective predefined part type;
• and
• each of the plurality of vectors is marked active when a magnitude of a respective vector is below a predefined vector truncating threshold;
• and
• generating a global pose map based on the feature map and the plurality of TPDF maps corresponding to the predefined part types, wherein the global pose map is configured to identify one or more human bodies having a plurality of body parts in a scene of the image.

A non-transitory computer-readable medium, having instructions stored thereon, which when executed by one or more processors cause the processors to perform a method for identifying human poses in an image;

• wherein the method comprises:
• obtaining the image;
• encoding the image into a feature map;
• converting the feature map into a plurality of Truncated Part Displacement Field (TPDF) maps corresponding to a plurality of predefined part types, where:
• each TPDF map corresponds to a respective predefined part type, and the image comprises one or more body parts of the respective predefined part type;
• each TPDF map comprises an x-axis displacement map and a y-axis displacement map, and represents a plurality of vectors connecting each position on the image to a closest body part among the one or more body parts of the respective predefined part type;
• and
• each of the plurality of vectors is marked active when a magnitude of a respective vector is below a predefined vector truncating threshold;
• and
• generating a global pose map based on the feature map and the plurality of TPDF maps corresponding to the predefined part types, wherein the global pose map is configured to identify one or more human bodies having a plurality of body parts in a scene of the image.