IP Library › Granted Patent US 11,715,301
Granted Patent B2
US 11,715,301 · App. 17/827,654 · Granted Aug 1, 2023

Visualization of non-visible phenomena

Inventors: Ying Bai (San Jose, CA); Kieran Dimond (San Jose, CA); James Christopher Schneider (Castro Valley, CA); Marco Cavallo (Santa Clara, CA); Arun Srivatsan Rangaprasad (Sunnyvale, CA); Tiejian Zhang (Santa Clara, CA)
Assignee: Apple Inc.
G06V20/20G02B27/017G06N20/00G06T7/70G06T19/006G06T2207/10028
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Quick Facts
Patent No.
US 11,715,301
App. No.
17/827,654
Granted
Aug 1, 2023
Kind
B2
Abstract

Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.

Claims (40)

1. A method, comprising:

identifying, using sensor data from a sensor of a device, a non-visible feature of a physical environment of the device;

identifying, by the device, a visual context for the non-visible feature; and

displaying, by the device, a visualization of the non-visible feature of the physical environment using the visual context and the sensor data, the visualization being overlaid on a location in the physical environment corresponding to the non-visible feature of the physical environment.

2. The method of claim 1 , wherein identifying the visual context comprises identifying the visual context based on a type of the sensor data.

3. The method of claim 1 , wherein identifying the visual context comprises identifying the visual context based on a type of an object at the location.

4. The method of claim 3 , further comprising identifying, by the device, the object and the type of the object.

5. The method of claim 4 , further comprising:

identifying, by the device, a physical feature of the object; and

displaying an adjustment indicator at a location associated with the physical feature of the object.

6. The method of claim 1 , wherein the location is a three-dimensional location in the physical environment, wherein the non-visible feature is hidden or exists outside of a visible light spectrum, and wherein the visualization comprises a representation of the non-visible feature in the visible light spectrum.

7. The method of claim 1 , wherein the sensor data comprises at least one of audio data, image data, wireless signal data, temperature data, airflow data, weather data, or gas sensor data.

8. The method of claim 1 , further comprising:

obtaining depth information for the physical environment using additional sensor data from an additional sensor, and

determining the location in the physical environment for overlay of the visualization based at least in part on the depth information.

9. The method of claim 1 , wherein the non-visible feature of the physical environment is a physical phenomenon in the physical environment that does not emit, reflect, or absorb light, in the visible light spectrum.

10. The method of claim 1 , wherein the non-visible feature of the physical environment is a physical element in the physical environment that does not emit, reflect, or absorb light, in the visible light spectrum, that is received at the device.

11. The method of claim 1 , wherein identifying the visual context for the non-visible feature comprises selecting the visual context from a plurality of visual contexts that are each stored at the device in connection with a respective non-visible feature type.

12. The method of claim 1 , further comprising:

providing the sensor data to a machine learning model; and

generating the visualization based on an output of the machine learning model.

13. The method of claim 1 , wherein the device comprises a head mounted device.

14. A device, comprising:

a sensor;

one or more processors; and

memory storing instructions that, when executed by the one or more processors, causes the one or more processors to:

identify, using sensor data from the sensor, a non-visible feature of a physical environment of the device;

identify a visual context for the non-visible feature; and

display a visualization of the non-visible feature of the physical environment using the visual context and the sensor data, the visualization being overlaid on a location in the physical environment corresponding to the non-visible feature of the physical environment.

15. The device of claim 14 , wherein the sensor comprises at least one of a microphone, a camera, a temperature sensor, a wireless communications antenna, a gas sensor, a depth sensor, a millimeter wave radar sensor, a light intensity sensor, an air quality sensor, a humidity sensor, a PH sensor, a moisture sensor, a flame sensor, or a steam detection sensor.

16. The device of claim 14 , further comprising a depth sensor, wherein the one or more processors are further configured to obtain depth information for the physical environment using the depth sensor, and to determine the location in the physical environment using the depth information.

17. The device of claim 14 , wherein the visual context comprises at least a portion that is adjustable based on the sensor data, and wherein the one or more processors are configured to display the visualization by:

adjusting the portion of the visual context based on the sensor data; and

displaying the visual context, with the portion adjusted based on the sensor data, at the location.

18. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a device, cause the one or more processors to:

identify, using sensor data from a sensor of the device, a non-visible feature of a physical environment of the device;

identify a visual context for the non-visible feature; and

display a visualization of the non-visible feature of the physical environment using the visual context and the sensor data, the visualization being overlaid on a location in the physical environment corresponding to the non-visible feature of the physical environment.

19. The non-transitory computer-readable medium of claim 18 , wherein the location is a three-dimensional location in the physical environment, wherein the non-visible feature is hidden or exists outside of a visible light spectrum, and wherein the visualization comprises a representation of the non-visible feature in the visible light spectrum.

20. The non-transitory computer-readable medium of claim 18 , wherein the sensor data comprises at least one of audio data, image data, wireless signal data, temperature data, airflow data, weather data, or gas sensor data.

Continuity (3)
Continuation 17378635 · Jul 16, 2021
Provisional Application 63063139 · Aug 7, 2020
Related Publication 20220292821A1 · Sep 15, 2022
Cited By (1)
US 12,328,174