Compressed Sensing for Gesture Tracking and Recognition with Radar

• US 20170097684A1
• Filed: 09/16/2016
• Published: 04/06/2017
• Est. Priority Date: 10/06/2015
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Lien, Jaime
• Application Number:
  US15/267,181
• Publication Number:
  US 20170097684A1
• Time in Patent Office: Days
• CPC Class Codes: G01S 13/88 Radar or analogous systems specially adapted for specific applications electromagnetic prospecting or detecting of objects, e.g. near-field detection, G01V3/00
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06V 40/28 Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113

Abstract

This document describes techniques using, and devices embodying, radar-based gesture recognition using compressed sensing. These techniques and devices can enable a great breadth of gestures and uses for those gestures, such as gestures to use, control, and interact with computing and non-computing devices, from software applications to refrigerators. The techniques and devices are capable of providing a radar field that can sense gestures from multiple actors at one time and through obstructions using compressed sensing, thereby improving gesture breadth and accuracy over many conventional techniques using less complex components.

Claims

1. A computer-implemented method comprising:

providing, by an emitter of a radar system, a radar field;

receiving, at a receiver of the radar system, one or more reflection signals caused by a gesture performed within the radar field;

digitally sampling the one or more reflection signals based, at least in part, on compressed sensing to generate digital samples;

analyzing, using the receiver, the digital samples at least by using one or more sensing matrices to extract information from the digital samples; and

determining the gesture using the information extracted from the digital samples.

2. The computer-implemented method as described in claim 1, wherein analyzing the digital samples further comprises reconstructing an approximation of a signal of interest from the digital samples.

3. The computer-implemented method as described in claim 1, wherein the digitally sampling comprises randomly capturing samples over a data acquisition window to capture N samples, the N samples comprising fewer samples than samples acquired using a Nyquist-Shannon sampling theorem based minimum sampling frequency over the data acquisition window.

4. The computer-implemented method as described in claim 1, wherein the radar field is configured to penetrate fabric but reflect from human tissue.

5. The computer-implemented method as described in claim 1, further comprising determining that the gesture is associated with a remote device and passing the gesture to the remote device.

6. The computer-implemented method as described in claim 1, the determining the gesture using the information extracted from the digital samples further comprising determining the gesture as a gesture performed by a particular actor.

7. The computer-implemented method as described in claim 1, the determining the gesture using the extracted information further comprising differentiating the gesture as being performed by a particular actor out of two or more actors.

8. The computer-implemented method as described in claim 1, further comprising, responsive to determining the gesture, passing the gesture to an application or operating system of a computing device performing the method effective to cause the application or operating system to receive an input corresponding to the gesture.

9. The computer-implemented method as described in claim 1, wherein the analyzing the digital samples further comprises applying an l₁ minimization technique.

10. A computer-implemented method comprising:

providing, using an emitter of a device, a radar field;

receiving, at the device, a reflection signal from interaction with the radar field;

processing, using the device, the reflection signal by;

acquiring N random samples of the reflection signal over a data acquisition window based, at least in part, on compressed sensing; and

extracting information from the N random samples by applying one or more sensing matrices to the N random samples;

determining a gesture associated with the interaction with the radar field; and

responsive to determining the gesture, passing the gesture to an application or operating system.

11. The computer-implemented method as described in claim 10, wherein the determining the gesture further comprises:

determining an identity of an actor causing the interaction with the radar field; and

determining the gesture is a pre-configured control gesture specifically associated with the actor and an application, and the method further comprises passing the pre-configured control gesture to the application effective to cause the application to be controlled by the gesture.

12. The computer-implemented method as described in claim 10, wherein the interaction includes reflections from human tissue having a layer of material interposed between the radar-based gesture recognition system and the human tissue, the layer of material including glass, wood, nylon, cotton, or wool.

13. The computer-implemented method as described in claim 10, the applying one or more sensing matrices to the N random samples further comprising accessing memory of the device to retrieve the one or more sensing matrices.

14. The computer-implemented method as described in claim 10, further comprising:

determining an identity of an actor causing the interaction with the radar field actor from multiple actors at one time; and

15. The computer-implemented method as described in claim 10, wherein passing the gesture to the application or operating system further comprises sending the gesture to a specific application out of multiple applications based upon an assignment of the gesture to the specific application.

16. A radar-based gesture recognition system comprising:

a radar-emitting element configured to provide a radar field;

an antenna element configured to receive reflections generated from interference with the radar field;

an analog-to-digital (ADC) converter configured to capture digital samples based, at least in part, on compressed sensing; and

at least one processor configured to process the digital samples sufficient to determine a gesture associated with the interference by extracting information from the digital samples using one or more sensing matrices.

17. The radar-based gesture recognition system as described in claim 16, the at least one processor further configured to determine the gesture associated with the interference as a pre-configured control gesture associated with a specific application out of multiple applications.

18. The radar-based gesture recognition system as described in claim 16, wherein at least one processor is further configured to reconstruct an approximation of a signal of interest from the digital samples.

19. The radar-based gesture recognition system as described in claim 18, wherein the approximation of the signal of interest is based, at least in part, on assuming a sparse representation of the signal of interest.

20. The radar-based gesture recognition system as described in claim 16, wherein at least one processor is further configured to determine an identity of a particular actor performing the gesture from multiple actors at one time.