Region extraction model learning apparatus, region extraction model learning method, and program

Abstract

Provided is technology for extracting a person region from an image, that can suppress preparation costs of learning data. Included are a composited learning data generating unit that generates, from already-existing learning data that is a set of an image including a person region and a mask indicating the person region, and a background image to serve as a background of a composited image, composited learning data that is a set of a composited image and a compositing mask indicating a person region in the composited image, and a learning unit that learns model parameters using the composited learning data. The composited learning data generating unit includes a compositing parameter generating unit that generates compositing parameters that are a set of an enlargement factor, a degree of translation, and a degree of rotation, using the mask of the learning data, and a composited image and compositing mask generating unit that extracts a compositing person region from an image in the learning data using a mask of the learning data, generates the composited image from the background image and the compositing person region, using the compositing parameters, generates the compositing mask from a mask generating image and the compositing person region that are the same size as the composited image, using the compositing parameters, and generates the composited learning data.