Method and apparatus for user and moving vehicle detection

Patent metadata

Field	Value
Publication number	US-10726281-B2
Application number	US-201514812411-A
Country	US
Kind code	B2
Filing date	Jul 29, 2015
Priority date	Jul 29, 2015
Publication date	Jul 28, 2020
Grant date	Jul 28, 2020

Abstract

An apparatus and method are disclosed for user and moving vehicle detection in which sensor data for a portable device is processed to determine whether the portable device is in a moving vehicle. Following a determination the portable device is in a moving vehicle, the sensor data is to characterize an association between the user and the portable device to determine whether the portable device is connected to the user. If the user is connected to the portable device, it is then determined if the portable device is being held in hand. If the portable device is held in hand, it is then determined if the user is operating the moving vehicle. Output from an image sensor of the portable device may be used in determining if the user is the operator.

First claim

What is claimed is:

1. A method for user and moving vehicle detection, the method comprising:
obtaining sensor data for a portable device from sensors integrated with the portable device, including at least one motion sensor configured to output data representing motion of the portable device;
performing an ordered sequence of determinations to improve resource conservation, wherein each determination is performed only if an immediately previous determination is confirmed, by:
a) processing motion sensor data obtained from only the portable device to determine whether the portable device is in a moving vehicle;
b) processing motion sensor data obtained from only the portable device to determine whether the portable device is connected to a user if the portable device is determined to be in the moving vehicle; and
c) processing motion sensor data to determine whether the portable device is hand held if it is determined the portable device is connected to the user, wherein processing the motion sensor data to determine whether the portable device is hand held comprises at least one of:
i) determining a device use case for the portable device by processing the motion sensor data;
ii) applying a machine learning technique to the motion sensor data; and
iii) applying a signal analysis technique to the motion sensor data.

2. The method of claim 1 , wherein processing motion sensor data to determine whether the portable device is in a moving vehicle comprises applying a machine learning technique.

3. The method of claim 2 , further comprising inputting features extracted from the processed motion sensor data to at least one stored classification model to determine a motion mode of the portable device.

4. The method of claim 3 , wherein the at least one stored classification model comprises extracted features developed during a training phase.

5. The method of claim 1 , wherein processing motion sensor data to determine whether the portable device is in a moving vehicle comprises applying a signal analysis technique.

6. The method of claim 5 , wherein the signal analysis technique comprises any one or any combination of the following: (i) a statistical analysis; (ii) a frequency-domain analysis; or (iii) a time-domain analysis.

7. The method of claim 5 , wherein the signal analysis technique comprises an analysis of at least one signal selected from the group consisting of an angular rotation signal, a signal derived from the angular rotation signal, an acceleration signal, and a signal derived from the acceleration signal.

8. The method of claim 1 , wherein the processing motion sensor data to determine whether the portable device is in a moving vehicle is based at least in part on motion sensor data that comprises inertial sensor data.

9. The method of claim 8 , further comprising obtaining supplemental sensor data for the portable device and processing the supplemental sensor data with the inertial sensor data.

10. The method of claim 1 , further comprising obtaining absolute navigational information for the portable device, wherein determining whether the portable device is in a moving vehicle is based at least in part on the absolute navigational information.

11. The method of claim 1 , wherein processing motion sensor data to determine whether the portable device is connected to the user comprises applying a machine learning technique.

12. The method of claim 11 , further comprising inputting features extracted from processed motion sensor data to at least one stored classification model to characterize if the portable device is connected to the user.

13. The method of claim 12 , wherein the at least one stored classification model comprises extracted features developed during a training phase.

14. The method of claim 1 , wherein processing motion sensor data to determine whether the portable device is connected to the user comprises applying a signal analysis technique.

15. The method of claim 14 , wherein the signal analysis technique comprises any one or any combination of the following: (i) a statistical analysis; (ii) a frequency-domain analysis; or (iii) a time-domain analysis.

16. The method of claim 14 , wherein the signal analysis technique comprises an analysis of at least one signal selected from the group consisting of an angular rotation signal, a signal derived from the angular rotation signal, an acceleration signal, and a signal derived from the acceleration signal.

17. The method of claim 1 , wherein determining whether the portable device is hand held comprises determining a device use case for the portable device.

18. The method of claim 1 , wherein processing the sensor data to determine whether the portable device is hand held comprises applying a machine learning technique.

19. The method of claim 18 , further comprising inputting features extracted from the processed sensor data to at least one stored classification model to determine whether the portable device is hand held.

20. The method of claim 19 , wherein the at least one stored classification model comprises extracted features developed during a training phase.

21. The method of claim 1 , wherein processing the sensor data to determine whether the portable device is hand held comprises applying a signal analysis technique.

22. The method of claim 21 , wherein the signal analysis technique comprises any one or any combination of the following: (i) a statistical analysis; (ii) a frequency-domain analysis; or (iii) a time-domain analysis.

23. The method of claim 21 , wherein the signal analysis technique comprises an analysis of at least one signal selected from the group consisting of an angular rotation signal, a signal derived from the angular rotation signal, an acceleration signal, and a signal derived from the acceleration signal.

24. The method of claim 1 , wherein the processing motion sensor data to determine whether the portable device is hand held is based at least in part on motion sensor data that comprises inertial sensor data.

25. The method of claim 24 , further comprising obtaining supplemental sensor data, wherein the determination of whether the portable device is hand held is further based at least in part on the supplemental sensor data.

26. The method of claim 25 , wherein the supplemental sensor data is obtained from at least one of an ambient light sensor and a proximity sensor.

27. The method of claim 25 , further comprising activating a source of the supplemental sensor data from a power save mode if it is determined the portable device is connected to the user.

28. The method of claim 1 , further comprising obtaining information regarding the portable device, wherein the determination of whether the portable device is hand held is further based at least in part on the information regarding the portable device.

29. The method of claim 28 , wherein the information regarding the portable device comprises a status of at least one application running on the portable device.

30. The method of claim 1 , further comprising obtaining image sensor data for the portable device if it is determined the portable device is hand held, processing the image sensor data, and determining whether the user of the portable device is operating the moving vehicle based at least in part on the processed image sensor data.

Assignees

• Invensense Inc

Inventors

• Ali Abdelrahman
• Elhoushi Mostafa
• Georgy Jacques
• Goodall Christopher
• Heshmati Ardalan
• Housholder Michael D

Classifications

• G06V10/806

  of extracted features · CPC title

• G06V40/28 Primary

  Recognition of hand or arm movements, e.g. recognition of deaf sign language (static hand signs G06V40/113) · CPC title

• G06V20/597

  Recognising the driver's state or behaviour, e.g. attention or drowsiness · CPC title

• G06F18/253

  of extracted features · CPC title

• G06F18/259

  Fusion by voting · CPC title