Information processing apparatus, information processing method, program

• US 10,565,510 B2
• Filed: 05/31/2016
• Issued: 02/18/2020
• Est. Priority Date: 01/28/2009
• Status: Active Grant

• Current Assignee: Sony Corporation (Sony Group Corp.)
• Original Assignee: Sony Corporation (Sony Group Corp.)
• Inventors: Fukumoto, Yasutaka, Murata, Makoto, Kurata, Masatomo, Katsu, Masanori
• Primary Examiner(s): Wong, Lut
• Application Number:
  US15/169,151
• Publication Number:
  US 20160275403A1
• Time in Patent Office: 1,358 Days
• Field of Search: 706 54
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/04 Inference or reasoning models

Abstract

There is provided an information processing apparatus including: a sensor data generator sensing a user behavior and generating sensor data corresponding to the user behavior; a behavior recognizing unit performing a predetermined threshold value process on the sensor data to recognize the behavior exhibited by the user and generating behavior information that is information indicating the behavior exhibited by the user; a behavior manager managing the behavior information generated by the behavior recognizing unit in correspondence with the time point at which the behavior corresponding to the behavior information is exhibited; and a behavior information post-processing unit performing a predetermined post-process on the behavior information managed by the behavior manager, wherein the behavior recognizing unit further includes a plurality of behavior determination units specified to specific behaviors exhibited by the user and generates the behavior information based on the determination results of the plurality of behavior determination units.

Claims

1. A non-transitory computer-readable medium having embodied thereon a program, which when executed by a computer causes the computer to execute an information processing method, the method comprising:

recognizing a user action of a user based on sensor data retrieved from a sensor, including recognizing the user action by using a characteristic detection process with respect to a predetermined processing for the user action from the sensor data, wherein the user action includes a vehicle boarding;

managing the recognized user action; and

causing a storage medium to store the recognized user action,

wherein the predetermined processing for the user action includes outputting an identification function based on the sensor data by using machine learning and identifying a vehicle type by using the identification function, and

wherein the predetermined processing for the user action further includes determining horizontal acceleration of the user and vertical acceleration of the user from the sensor data and determining a horizontal direction variance value of the horizontal acceleration of the user over a predetermined period of time and a vertical direction variance value of the vertical acceleration of the user over the predetermined period of time and comparing the horizontal direction variance value and the vertical direction variance value to determine a smaller variance value, and comparing an integration value representing integration over the predetermined period of time of the smaller variance value resulting from the comparison between the horizontal direction variance value and the vertical direction variance value with a minimum determination threshold for the user action.

2. The non-transitory computer-readable medium according to claim 1, wherein the managing of the recognized user action further comprises managing a time information related to the user action.

3. The non-transitory computer-readable medium according to claim 1, wherein the recognized user action is retrieved from an external server.

4. The non-transitory computer-readable medium according to claim 1, wherein a user action of another user is retrieved from an external server.

5. The non-transitory computer-readable medium according to claim 4, wherein the managing of the recognized user action further comprises managing the user action of the other user.

6. The non-transitory computer-readable medium according to claim 5, wherein the managing of the recognized user action further comprises causing a display to display the user action of the other user.

7. The non-transitory computer-readable medium according to claim 1, wherein the managing of the recognized user action further comprises managing the user action recognized in the past.

8. The non-transitory computer-readable medium according to claim 1, wherein the managing of the recognized user action further comprises causing a display to display the user action of the user.

9. The non-transitory computer-readable medium according to claim 1, wherein the vehicle boarding includes boarding at least one vehicle selected from a group consisting of a train, a car, a bus and a bicycle.

10. The non-transitory computer-readable medium according to claim 1, wherein the user action further comprises at least one of walking and running.

11. The non-transitory computer-readable medium according to claim 1, wherein the predetermined processing for the user action further includes determining at least one of a frequency corresponding to the horizontal acceleration of the user or a frequency corresponding to the vertical acceleration of the user.

12. An information processing apparatus comprising:

circuitry configured to

recognize a user action of a user based on sensor data retrieved from a sensor, including recognizing the user action by using a characteristic detection process with respect to a predetermined processing for the user action from the sensor data, wherein the user action includes a vehicle boarding,

manage the recognized user action, and

cause a storage medium to store the recognized user action,

wherein the predetermined processing for the user action includes outputting an identification function based on the sensor data by using machine learning and identifying a vehicle type by using the identification function, and

wherein the predetermined processing for the user action further includes determining horizontal acceleration of the user and vertical acceleration of the user from the sensor data and determining a horizontal direction variance value of the horizontal acceleration of the user over a predetermined period of time and a vertical direction variance value of the vertical acceleration of the user over the predetermined period of time and comparing the horizontal direction variance value and the vertical direction variance value to determine a smaller variance value, and comparing an integration value representing integration over the predetermined period of time of the smaller variance value resulting from the comparison between the horizontal direction variance value and the vertical direction variance value with a minimum determination threshold for the user action.

13. An information processing method, performed via at least one processor, the method comprising:

recognizing a user action of a user based on sensor data retrieved from a sensor, including recognizing the user action by using a characteristic detection process with respect to a predetermined processing for the user action from the sensor data, wherein the user action includes a vehicle boarding;

managing the recognized user action; and

causing a storage medium to store the recognized user action,

wherein the predetermined processing for the user action includes outputting an identification function based on the sensor data by using machine learning and identifying a vehicle type by using the identification function, and

wherein the predetermined processing for the user action further includes determining horizontal acceleration of the user and vertical acceleration of the user from the sensor data and determining a horizontal direction variance value of the horizontal acceleration of the user over a predetermined period of time and a vertical direction variance value of the vertical acceleration of the user over the predetermined period of time and comparing the horizontal direction variance value and the vertical direction variance value to determine a smaller variance value, and comparing an integration value representing integration over the predetermined period of time of the smaller variance value resulting from the comparison between the horizontal direction variance value and the vertical direction variance value with a minimum determination threshold for the user action.