PERSON ATTRIBUTE ESTIMATION SYSTEM AND LEARNING-USE DATA GENERATION DEVICE

1 . A person attribute estimation system comprising:

an attribute estimation unit for estimating an attribute of an attribute estimation target person shown in the image generated by a camera, by using an estimation model;

an image capturing environment data acquisition unit for acquiring image capturing environment data indicating an image capturing environment of the attribute estimation target person by the camera;

a standard image acquisition unit for acquiring a standard image that is a person image;

a pseudo-site image generation unit for generating a pseudo-site image reflecting the image capturing environment in the standard image by processing data of the standard image according to the image capturing environment data; and

a learning unit for performing learning of the estimation model by using the pseudo-site image.

2 . The person attribute estimation system according to claim 1 , wherein the learning unit performs learning of the estimation model by using, as learning-use image data, a pseudo-site image capturing image that is obtained by capturing a subject showing the pseudo-site image by the camera in the image capturing environment of the attribute estimation target person by the camera.

3 . The person attribute estimation system according to claim 1 , wherein the learning unit performs learning of the estimation model by using, as learning-use image data, the pseudo-site image generated by the pseudo-site image generation unit.

4 . The person attribute estimation system according to claim 1 ,

wherein attribute data indicating an attribute of a person who is a subject is associated with the standard image, and

wherein the learning unit performs learning of the estimation model by using, as learning-use correct attribute data, attribute data corresponding to the standard image used for generation of the pseudo-site image.

5 . The person attribute estimation system according to claim 1 , further comprising:

an image capturing environment estimation unit for calculating the image capturing environment data based on the image generated by the camera,

wherein the image capturing environment data acquisition unit acquires the image capturing environment data calculated by the image capturing environment estimation unit.

6 . The person attribute estimation system according to claim 1 ,

wherein the image capturing environment data includes data indicating an illumination state of a location where the attribute estimation target person is to be captured by the camera, and

wherein the pseudo-site image generation unit generates the pseudo-site image by transforming the standard image according to the data indicating the illumination state.

7 . The person attribute estimation system according to claim 1 ,

wherein the attribute estimation unit is for estimating an attribute of a person appearing in the image generated by the camera based on a partial image of a face region in the image,

wherein the image capturing environment data includes data regarding orientation of a face when the attribute estimation target person is captured by the camera,

wherein the standard image is an image including a face of a person, and

wherein the pseudo-site image generation unit generates the pseudo-site image by transforming orientation of the face in the standard image according to the data regarding orientation of a face.

8 . The person attribute estimation system according to claim 1 , wherein the image capturing environment data is image capturing environment data for each of one or more representative person detection regions in the image generated by the camera.

9 . The person attribute estimation system according to claim 8 ,

wherein the pseudo-site image generation unit generates the pseudo-site image for each of the representative person detection regions by using the image capturing environment data for each of the representative person detection regions,

wherein the learning unit performs learning of the estimation model for each of the representative person detection regions, and

wherein the attribute estimation unit estimates an attribute of a person by selecting the estimation model according to a detection position of the person shown in the image generated by the camera.

10 . A learning-use data generation device for generating learning-use data to be used in learning of an estimation model, for attribute estimation for a person, which is to be used by a person attribute estimation system including an attribute estimation unit for estimating an attribute of an attribute estimation target person shown in the image generated by a camera, the learning-use data generation device comprising:

an image capturing environment data acquisition unit for acquiring image capturing environment data indicating an image capturing environment of the attribute estimation target person by the camera;

a standard image acquisition unit for acquiring a standard image that is a person image; and

a pseudo-site image generation unit for generating a pseudo-site image reflecting the image capturing environment in the standard image, by processing data of the standard image according to the image capturing environment data,

wherein the learning-use data is generated by using the pseudo-site image or a pseudo-site image capturing image that is obtained by capturing a subject showing the pseudo-site image by the camera in an environment where the attribute estimation target person is to be captured by the camera.

11 . The learning-use data generation device according to claim 10 , wherein the learning-use data includes the pseudo-site image or the pseudo-site image capturing image which is learning-use image data, and attribute data that is correct attribute data for learning-use and that is associated with the standard image that was used in generation of the pseudo-site image.

12 . A person attribute estimation method for causing an attribute of an attribute estimation target person shown in an image generated by a camera to be estimated by using an estimation model, the person attribute estimation method comprising:

learning the estimation model by using a pseudo-site image reflecting an image capturing environment of the attribute estimation target person by the camera in a standard image that is a person image generated by processing the standard image according to image capturing environment data indicating the image capturing environment.

13 . The person attribute estimation method according to claim 12 , wherein, in the learning, learning of the estimation model is further performed by using, as learning-use image data, a pseudo-site image capturing image that is obtained by capturing a subject showing the pseudo-site image by the camera in the image capturing environment of the attribute estimation target person by the camera.

14 . The person attribute estimation method according to claim 12 , wherein, in the learning, learning of the estimation model is further performed by using the pseudo-site image as learning-use image data.

15 . The person attribute estimation method according to claim 12 ,

wherein attribute data indicating an attribute of a person who is a subject is associated with the standard image, and

wherein, in the learning, learning of the estimation model is further performed by using, as learning-use correct attribute data, attribute data corresponding to the standard image used for generation of the pseudo-site image.

16 . The person attribute estimation method according to claim 12 , wherein, in the learning, the image capturing environment data is further calculated based on the image generated by the camera.

17 . The person attribute estimation method according to claim 12 ,

wherein the image capturing environment data includes data indicating an illumination state of a location where the attribute estimation target person is to be captured by the camera, and

wherein, in the learning, the pseudo-site image is further generated by transforming the standard image according to the data indicating the illumination state.

18 . The person attribute estimation method according to claim 12 ,

wherein the image capturing environment data includes data regarding orientation of a face when the attribute estimation target person is captured by the camera,

wherein the standard image is an image including a face of a person, and

wherein, in the learning, the pseudo-site image is further generated by transforming orientation of the face in the standard image according to the data regarding orientation of a face.

19 . The person attribute estimation method according to claim 12 , wherein the image capturing environment data is image capturing environment data for each of one or more representative person detection regions in the image generated by the camera.

20 . The person attribute estimation method according to claim 19 , wherein, in the learning, a pseudo-site image for each of the representative person detection regions is further generated by using the image capturing environment data for each of the representative person detection regions, learning of the estimation model for each of the representative person detection regions is performed, and an attribute of a person is estimated by selecting the estimation model according to a detection position of the person shown in the image generated by the camera.

21 . A learning-use data generation method for generating learning-use data to be used in learning of an estimation model, for attribute estimation for a person, which is to be used by a person attribute estimation system including an attribute estimation unit for estimating an attribute of an attribute estimation target person shown in an image generated by a camera, the learning-use data generation method comprising:

generating the learning-use data by using a pseudo-site image generated by processing data of a standard image that is a person image, according to image capturing environment data indicating an image capturing environment of the attribute estimation target person by the camera.

22 . The learning-use data generation method according to claim 21 , wherein the learning-use data includes the pseudo-site image or a pseudo-site image capturing image which is learning-use image data and attribute data that is learning-use correct attribute data and that is associated with the standard image that was used in generation of the pseudo-site image.