Inference model construction method, inference model construction device, recording medium, configuration device, and configuration method

An inference model construction device for constructing an inference model for inferring deformation, in a defined state, of each part of a two-dimensional image of a target object, with respect to a representation model for realizing a rendering representation corresponding to a state different from a reference state of the target object by deforming the part of the two-dimensional image corresponding to the reference state, wherein the defined state differs from the reference state, wherein

• the representation model is defined by defining deformation of each part of the two-dimensional image in at least one defined state, and is configured to realize a rendering representation corresponding to at least a state between the reference state and the defined state,
• the deformation of each part in the representation model is controlled by a mode of a distribution of control points set for the part,
• the inference model construction device comprises:
• at least one processor;
• and
• a memory configured to store instructions that, when executed by the at least one processor, cause the at least one processor to function as:
• an obtaining unit configured to obtain the distribution of the control points pertaining to the reference state and the distribution of the control points pertaining to the defined state with respect to a defined representation model, which is the representation model that has been defined;
• an extraction unit configured to extract a first feature value based on the distribution of the control points pertaining to the reference state obtained by the obtaining unit;
• an estimation unit configured to estimate a second feature value based on the distribution of the control points pertaining to the reference state and the distribution of the control points pertaining to the defined state that are obtained by the obtaining unit;
• and
• a learning unit configured to machine-learn the distribution of the control points pertaining to the defined state obtained by the obtaining unit while using, as a label, the first feature value extracted by the extraction unit and the second feature value estimated by the estimation unit, and constructing an inference model based on a result of the leaning performed with respect to a plurality of the defined representation models, wherein
• the second feature value includes information indicating an amount of deformation of translational components and an amount of deformation of non-translational components regarding deformation from the reference state to the defined state,
• the target object includes a head of a character,
• the information indicating the amount of the deformation of the translational components in the second feature value is estimated based on an amount of movement of at least one control point set for a third-type part constituting the head of the character, between the distribution of the control points pertaining to the reference state and the distribution of the control points pertaining to the defined state, and
• the information indicating the amount of the deformation of the non-translational components in the second feature value is estimated based on a difference between a plurality of control points set for a fourth-type part constituting the head of the character, in an amount of movement between the distribution of the control points pertaining to the reference state and the distribution of the control points pertaining to the defined state.