Learning method, storage medium, and image processing device
AssigneeKabushiki Kaisha Toshiba
InventorsNao MISHIMA, Masako KASHIWAGI
Life of this patent
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Abstract
According to one embodiment, a learning method includes acquiring first and second images and causing a statistical model to learn based on a first distance output from the statistical model by inputting a first region of the first image, and a second distance output from the statistical model by inputting a second region of the second image. A relationship in size between a third distance to a subject in the first image and a fourth distance to the subject included in the second image is already known. The causing includes causing the statistical model to learn such that a relationship in size between the first and the second distances is equal to a relationship in size between the third and the fourth distances.
Claims15
A learning method of causing a statistical model for inputting an image including a subject and outputting a distance to the subject to learn, the learning method comprising:
- acquiring first and second images each including the subject captured by a capture device;
- and
- causing the statistical model to learn based on a first distance output from the statistical model by inputting a first region that is at least a part of the first image, and a second distance output from the statistical model by inputting a second region that is at least a part of the second image, wherein
- a relationship in size between a third distance to the subject included in the first image and a fourth distance to the subject included in the second image is already known,
- the causing includes causing the statistical model to learn such that a relationship in size between the first distance and the second distance is equal to a relationship in size between the third distance and the fourth distance.
A non-transitory computer-readable storage medium having stored thereon a computer program which is executable by a computer and causes a statistical model for inputting an image including a subject and outputting a distance to the subject to learn, the computer program comprising instructions capable of causing the computer to execute functions of:
- acquiring first and second images each including the subject captured by a capture device;
- and
- causing the statistical model to learn based on a first distance output from the statistical model by inputting a first region that is at least a part of the first image, and a second distance output from the statistical model by inputting a second region that is at least a part of the second image, wherein
- a relationship in size between a third distance to the subject included in the first image and a fourth distance to the subject included in the second image is already known,
- the causing includes causing the statistical model to learn such that a relationship in size between the first distance and the second distance is equal to a relationship in size between the third distance and the fourth distance.
An image processing device for causing a statistical model for inputting an image including a subject and outputting a distance to the subject to learn, the image processing device comprising:
- a processor configured to:
- acquire first and second images including the subject captured by a capture device;
- and
- cause the statistical model to learn based on a first distance output from the statistical model by inputting a first region that is at least a part of the first image, and a second distance output from the statistical model by inputting a second region that is at least a part of the second image, wherein
- a relationship in size between a third distance to the subject included in the first image and a fourth distance to the subject included in the second image is already known,
- the causing includes causing the statistical model to learn such that a relationship in size between the first distance and the second distance is equal to a relationship in size between the third distance and the fourth distance.
Dependencies are inferred from the claim text.