Information processing device, eyesight test system, information processing method
An information processing device for estimating eyesight of a person comprises a processor coupled to memory storing machine readable instructions. The processor obtains image data representing an image of an eye and inputs the data into a machine learning algorithm trained to estimate eyesight characteristics from eye images. The system estimates the person's eyesight by determining at least one of myopia, hyperopia, and astigmatism based on the image data and algorithm output. The invention addresses limitations of traditional manual eyesight tests that are prone to human error and subjective patient feedback. The machine learning algorithm analyzes eye relaxation states and micromovements that indicate optimal vision correction, enabling objective automated eyesight assessment deployable in remote locations or consumer devices.
1 . An information processing device for estimating an eyesight of a person, comprising:
a processor coupled to a memory that stores machine readable instructions thereon which, when executed by the processor, causes the processor to
obtain image data representing an image of an eye of the person;
input the image data into a machine learning algorithm trained to estimate eyesight characteristics from eye images based on visual features of the eye including at least one of eyeball shape and eye micromovements; and
estimate, based on the image data and an output of the machine learning algorithm, the eyesight of the person by determining at least one of myopia, hyperopia, and astigmatism of the eye.
2 . The information processing device according to claim 1 , wherein estimating the eyesight includes estimating whether the person sees sharply.
3 . The information processing device according to claim 1 , wherein the circuitry is configured to predict, based on the image data and the estimate eyesight, a parameter of an eyesight correction device.
4 . The information processing device according to claim 1 , wherein the circuitry is configured to predict, based on the image data and the estimated eyesight, an eyesight degradation prevention exercise.
5 . The information processing device according to claim 1 , wherein the image data represent a plurality of consecutive images, and wherein the circuitry is configured to estimate, based on the image data and the estimated eyesight, an eye-movement disorder.
6 . The information processing device according to claim 1 , wherein the circuitry is configured to output information regarding at least one of an estimation of the eyesight, a parameter of an eyesight correction device, an eyesight degradation prevention exercise and an eye-movement disorder.
7 . The information processing device according to claim 1 , comprising a camera configured to acquire the image data.
8 . The information processing device according to claim 7 , wherein the camera is a color camera, or wherein the camera is an infrared camera and the image data are infrared image data, or wherein the camera is an event camera and the image data are event image data.
9 . The information processing device according to claim 1 , wherein the information processing device is a mobile device, or wherein the information processing device is smart glasses.
10 . An eyesight test system, comprising:
a lens changing device configured to hold and exchange a lens for testing an eyesight of a person; and
a camera configured to acquire image data representing an image of an eye of the person;
an information processing device for estimating the eyesight of the person, including a processor coupled to a memory that stores machine readable instructions thereon which, when executed by the processor, causes the processor to obtain image data representing an image of an eye of the person;
input the image data into a machine learning algorithm trained to estimate eyesight characteristics from eye images based on visual features of the eye including at least one of eyeball shape and eye micromovements; and
estimate, based on the image data and an output of the machine learning algorithm, the eyesight of the person by determining at least one of myopia, hyperopia, and astigmatism of the eye.
11 . The eyesight test system according to claim 10 , wherein the lens changing device is configured to exchange the lens automatically with a next lens, and wherein the camera is configured to acquire next image data representing a next image after the next lens is placed.
12 . An information processing method for estimating an eyesight of a person, comprising:
obtaining image data representing an image of an eye of the person;
inputting the image data into a machine learning algorithm trained to estimate eyesight characteristics from eye images based on visual features of the eye including at least one of eyeball shape and eye micromovements; and
estimating, based on the image data and an output of the machine learning algorithm, the eyesight of the person by determining at least one of myopia, hyperopia, and astigmatism of the eye.
13 . The information processing method according to claim 12 , wherein estimating the eyesight includes estimating whether a sharp image is obtained on the person's retina.
14 . The information processing method according to claim 12 , comprising predicting, based on the image data and the estimate eyesight, a parameter of an eyesight correction device and/or an eyesight degradation prevention exercise.
15 . The information processing method according to claim 12 , wherein the image data represent a plurality of consecutive images, comprising estimating, based on the image data and the estimated eyesight, an eye-movement disorder.
16 . The information processing method according to claim 12 , comprising acquiring the image data by a camera.
17 . The information processing device of claim 1 , wherein the machine learning algorithm is an artificial neural network, wherein the artificial neural network is a convolutional neural network, a decision tree, or a support vector machine.