A three-dimensional shape data generation apparatus includes: a processor configured to obtain two-dimensional shape data representing a two-dimensional shape corresponding to a three-dimensional shape of a target to which attribute information is to be assigned, obtain the attribute information of the two-dimensional shape, and assign the obtained attribute information to at least some three-dimensional elements among plural three-dimensional elements representing the three-dimensional shape to generate three-dimensional shape data.

A three-dimensional shape data generation apparatus includes: a processor configured to obtain two-dimensional shape data representing a two-dimensional shape corresponding to a three-dimensional shape of a target to which attribute information is to be assigned, obtain the attribute information of the two-dimensional shape, and assign the obtained attribute information to at least some three-dimensional elements among plural three-dimensional elements representing the three-dimensional shape to generate three-dimensional shape data.

A package measuring apparatus includes a depth sensor, the package having a rectangular parallelepiped shape and placed on a mounting table, and at least one processor. The processor obtains spatial coordinates of four vertices within a space in which the center of the depth sensor is set as the point of origin based on data of a distance from the depth sensor to each of the four vertices and data of a position of each sensor element of the depth sensor corresponding to each of the four vertices. The processor calculates, based on the spatial coordinates of the four vertices, a length of each of three sides defined between a first vertex and three other vertices.

A package measuring apparatus includes a depth sensor, the package having a rectangular parallelepiped shape and placed on a mounting table, and at least one processor. The processor obtains spatial coordinates of four vertices within a space in which the center of the depth sensor is set as the point of origin based on data of a distance from the depth sensor to each of the four vertices and data of a position of each sensor element of the depth sensor corresponding to each of the four vertices. The processor calculates, based on the spatial coordinates of the four vertices, a length of each of three sides defined between a first vertex and three other vertices.

Estimating a material property parameter of fabric involves receiving information including a three-dimensional (3D) contour shape of fabric placed over a 3D geometric object, estimating a material property parameter of the fabric used for representing drape shapes of 3D clothes made by the fabric by applying the information to a trained artificial neural network, and providing the material property parameter of the fabric.

Estimating a material property parameter of fabric involves receiving information including a three-dimensional (3D) contour shape of fabric placed over a 3D geometric object, estimating a material property parameter of the fabric used for representing drape shapes of 3D clothes made by the fabric by applying the information to a trained artificial neural network, and providing the material property parameter of the fabric.

A detection device includes: a detector that detects an object from one viewpoint; an reliability calculator that calculates reliability information on the object from the one viewpoint; an information calculator that uses detection results of the detector to calculate model information including at least one of shape information and texture information, on the object, from the one viewpoint; and an information processor that uses first object information including the model information or source data used for generation of the model information, and the reliability information, so as to generate second object information having a reduced data amount of the model information or the source data.

A detection device includes: a detector that detects an object from one viewpoint; an reliability calculator that calculates reliability information on the object from the one viewpoint; an information calculator that uses detection results of the detector to calculate model information including at least one of shape information and texture information, on the object, from the one viewpoint; and an information processor that uses first object information including the model information or source data used for generation of the model information, and the reliability information, so as to generate second object information having a reduced data amount of the model information or the source data.

An image processing method includes: detecting a plurality of feature lines from a first image captured from a first position; specifying, based on a positional relationship between the plurality of feature lines and a plurality of projection lines generated by projecting each of a plurality of line segments onto the first image, a feature line representing a defective portion of a shape of an object; setting a plurality of candidate positions based on the first position, each of the plurality of candidate positions being a candidate for a second position at which a second image is captured; calculating an evaluation value of each of the plurality of candidate positions; determining any of the plurality of candidate positions based on the evaluation value of each of the plurality of candidate positions; and outputting first information to be used in recognition of the determined candidate position.

An image processing method includes: detecting a plurality of feature lines from a first image captured from a first position; specifying, based on a positional relationship between the plurality of feature lines and a plurality of projection lines generated by projecting each of a plurality of line segments onto the first image, a feature line representing a defective portion of a shape of an object; setting a plurality of candidate positions based on the first position, each of the plurality of candidate positions being a candidate for a second position at which a second image is captured; calculating an evaluation value of each of the plurality of candidate positions; determining any of the plurality of candidate positions based on the evaluation value of each of the plurality of candidate positions; and outputting first information to be used in recognition of the determined candidate position.