Training a neural network with representations of user interface devices
An example wearable display system can be capable of determining a user interface (UI) event with respect to a virtual UI device (e.g., a button) and a pointer (e.g., a finger or a stylus) using a neural network. The wearable display system can render a representation of the UI device onto an image of the pointer captured when the virtual UI device is shown to the user and the user uses the pointer to interact with the virtual UI device. The representation of the UI device can include concentric shapes (or shapes with similar or the same centers of gravity) of high contrast. The neural network can be trained using training images with representations of virtual UI devices and pointers.
1. A system comprising:
computer-readable memory storing executable instructions; and
one or more processors programmed by the executable instructions to at least:
receive a plurality of images, wherein:
an image of the plurality of images comprises a pointer of a plurality of pointers,
the image is associated with a virtual user interface (UI) device of a plurality of virtual UI devices at an image location on the image, and
the image is associated with a UI event of a plurality of UI events with respect to the virtual UI device and the pointer in the image;
render a representation of the virtual UI device onto the image at the image location to generate a training image; and
generate a training set comprising input data and corresponding target output data, wherein the input data comprises the training image, and wherein the corresponding target output data comprises the UI event.
2. The system of claim 1 , wherein the one or more processors is further programmed to train, using the training set, a machine learning model for determining a UI event associated with the virtual UI device and the pointer.
3. The system of claim 1 , wherein the representation of the virtual UI device comprises a plurality of shapes of high contrasts.
4. The system of claim 3 , wherein the centers of gravity of shapes of the plurality of shapes are within a threshold distance of each other.
5. The system of claim 4 , wherein the threshold distance is 0.
6. The system of claim 3 , wherein a first shape of the plurality of shapes is associated with a first color, wherein a second shape of the plurality of shapes is associated with a second color, and wherein the first shape is adjacent to the second shape.
7. The system of claim 6 , wherein the second shape is partially transparent.
8. The system of claim 7 , wherein a first region of the second shape is associated with a first transparency value, and wherein a second region of the second shape is associated with a second transparency value.
9. The system of claim 8 , wherein the second region of the second shape is further away from the first region of the second shape, and wherein the second transparency value is smaller than the first transparency value.
10. The system of claim 6 , wherein the second shape is within the first shape.
11. The system of claim 6 , wherein a third shape of the plurality of shapes has a third color, and wherein the first shape is adjacent to the third shape.
12. The system of claim 1 , wherein the UI event corresponds to a state of a plurality of states of the virtual UI device.
13. The system of claim 12 , wherein the plurality of states comprises activation or non-activation of the virtual UI device.
14. The system of claim 1 , wherein the plurality of virtual UI devices comprises a button, an updown, a spinner, a picker, a radio button, a radio button list, a checkbox, a picture box, a checkbox list, a dropdown list, a dropdown menu, a selection list, a list box, a combo box, a textbox, a slider, a link, a keyboard key, a switch, a slider, a touch surface, or a combination thereof.
15. The system of claim 1 , wherein the plurality of UI pointers comprises an object associated with a user or a part of the user.
16. The system of claim 15 , wherein the object associated with the user comprises a pointer, a pen, a pencil, a marker, a highlighter, or a combination thereof, and wherein the part of the user comprises a finger of the user.
17. A method comprising:
receiving a plurality of images, wherein:
an image of the plurality of images comprises a pointer of a plurality of pointers,
the image is associated with a virtual user interface (UI) device of a plurality of virtual UI devices at an image location on the image, and
the image is associated with a UI event of a plurality of UI events with respect to the virtual UI device and the pointer in the image;
rendering a representation of the virtual UI device onto the image at the image location to generate a training image; and
generating a training set comprising input data and corresponding target output data, wherein the input data comprises the training image, and wherein the corresponding target output data comprises the UI event.
18. The method of claim 17 , further comprising:
training, using the training set, a machine learning model for determining a UI event associated with the virtual UI device and the pointer.
19. The method of claim 17 , wherein the UI event corresponds to a state of a plurality of states of the virtual UI device.
20. The method of claim 17 , wherein the plurality of UI pointers comprises an object associated with a user or a part of the user.