Multi-sensor based user interface

1. An apparatus for gesture detection and recognition, the apparatus comprising:

a processing element;

a radar sensor;

a depth sensor; and

an optical sensor, wherein the radar sensor, the depth sensor, and the optical sensor are coupled to the processing element, wherein the processing element is configured to identify a type of gesture, wherein the data acquired with the radar sensor is registered to the data acquired with the depth sensor to produce registration information for the radar sensor and the depth sensor, wherein the registration information is used with calibration information for the optical sensor and the depth sensor to produce a velocity image comprising a plurality of pixels and a velocity value per pixel in the plurality of pixels, and wherein velocity values of the velocity image are used by the processing element to classify the gesture.

2. The apparatus as described in claim 1 , wherein the radar sensor is in an always-on mode during a period in which the depth sensor and the optical sensor are turned off, wherein the depth sensor and the optical sensor are activated and a gesture recognition process to identify the type of the gesture is performed only in response to the radar sensor detecting an amount of motion above a non-zero threshold amount that lasts for at least a non-zero threshold length of time.

3. The apparatus as described in claim 2 , wherein the threshold amount of motion is selected from the group consisting of: a threshold velocity of the motion; and a threshold distance of the motion.

4. The apparatus as described in claim 1 , wherein the radar sensor, the depth sensor, and the optical sensor are a portion of a user interface device of a vehicle.

5. The apparatus as described in claim 1 , wherein a portion of the processing element is configured to function as a deep neural network (DNN).

6. The apparatus as described in claim 5 , wherein the DNN comprises two 3D convolutional layers and two fully-connected layers.

7. The apparatus as described in claim 1 , wherein the radar sensor, the depth sensor, and the optical sensor are configured for gesture detection and recognition under low light conditions.

8. The apparatus as described in claim 1 , wherein the processing element is a graphics processing unit (GPU).

9. The apparatus as described in claim 1 , wherein the radar sensor, the depth sensor, and the optical sensor are configured for gesture detection and recognition within a range of one meter.

10. The apparatus as described in claim 1 , wherein the gesture is a dynamic hand gesture and wherein further the processing element is configured to automatically determine a command associated with the dynamic hand gesture.

11. A system for hand gesture recognition, the system comprising:

a processor;

a first sensor comprising a radar;

a second sensor comprising a depth sensor; and

a third sensor comprising an optical sensor, wherein the first sensor, the second sensor, and third sensor are coupled to the processor, wherein further the processor is configured to identify a type of gesture of a hand by combining data acquired with the first sensor, data acquired with the second sensor, and data acquired with the third sensor, wherein the data acquired with the radar is registered to the data acquired with the depth sensor to produce registration information for the radar sensor and the depth sensor, wherein registering the data acquired with the radar to the data acquired with the depth sensor comprises transforming three-dimension (3D) coordinates of the data acquired with the radar to the depth sensor's coordinate frame, wherein the registration information is used with calibration information for the optical sensor and the depth sensor to produce a velocity image comprising a velocity value per pixel in the velocity image, and wherein velocity values for a portion of the velocity image corresponding to the hand are used by the processing element to identify the type of the gesture.

12. The system as described in claim 11 , wherein the radar sensor is in an always-on mode during a period in which the depth sensor and the optical sensor are turned off, wherein the depth sensor and the optical sensor are activated and a gesture recognition process to identify the type of the gesture is performed only in response to the radar sensor detecting an amount of motion above a threshold amount that lasts for at least a threshold length of time.

13. The system as described in claim 12 , wherein the threshold amount of motion is selected from the group consisting of: a threshold velocity of the motion; and a threshold distance of the motion.

14. The system as described in claim 11 , wherein the first sensor, the second sensor, and the third sensor are a portion of a user interface device for use in a vehicle.

15. The system as described in claim 11 , wherein a portion of the processor is configured to function as a deep neural network (DNN).

16. The system as described in claim 11 , wherein the processor is a graphics processing unit (GPU).

17. The system as described in claim 11 , wherein hand gesture is a dynamic hand gesture and wherein further the processing element is configured to automatically determine a command associated with the dynamic hand gesture.

18. A method for hand gesture recognition, the method comprising:

receiving, at a processor, data from a first sensor comprising a radar;

receiving, at the processor, data from a second sensor comprising a depth sensor;

receiving, at the processor, data from a third sensor comprising an optical sensor;

the processor combining the data from the first sensor, the data from the second sensor, and the data from the third sensor, wherein the data acquired with the radar is registered to the data acquired with the depth sensor to produce registration information for the radar sensor and the depth sensor;

the processor using the registration information with calibration information for the optical sensor and the depth sensor to produce a velocity image comprising a plurality of pixels and a velocity value per pixel in the plurality of pixels; and

the processor identifying a type of gesture of a hand using velocity values for a portion of the velocity image corresponding to the hand.

19. The method of claim 18 , wherein registering the data acquired with the radar to the data acquired with the depth sensor comprises transforming three-dimension (3D) coordinates of the data acquired with the radar to the depth sensor's coordinate frame.

20. The method of claim 18 , further comprising the processor determining a command associated with the gesture.