TRENDS AND RULES COMPLIANCE WITH DEPTH VIDEO

• US 20140140590A1
• Filed: 11/21/2012
• Published: 05/22/2014
• Est. Priority Date: 11/21/2012
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Wilson, Andrew, Hodges, Stephen Edward
• Application Number:
  US13/683,981
• Publication Number:
  US 20140140590A1
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands

Abstract

An instruction-storage machine holds instructions that, when executed by a logic machine, cause the logic machine to find a human subject in depth data acquired with one or more depth cameras and to compute an aspect of the human subject from the depth data. The instructions further cause the logic machine to determine, based on the computed aspect, whether the human subject is complying with or deviating from a predefined rule, and to issue notification if the human subject is deviating from the rule. In another example, the instructions cause the logic machine to identify a trend based on the computed aspect and to report the identified trend.

Claims

1. An instruction-storage machine holding instructions that, when executed by a logic machine, cause the logic machine to:

find a human subject in depth data acquired with one or more depth cameras arranged to image an environment;

compute an aspect of the human subject from the depth data;

based on the computed aspect, determine whether the human subject is complying with or deviating from a predefined rule; and

issue a notification if the human subject is deviating from the rule.

2. The instruction-storage machine of claim 1 wherein the rule is defined by a person, and wherein the notification is a message issued to that person.

3. The instruction-storage machine of claim 1 wherein the person to whom the notification is issued is the found human subject or another person in the environment.

4. The instruction-storage machine of claim 1 wherein the rule is machine learned based on prior computation of the aspect from prior depth data acquired with the one or more depth cameras.

5. The instruction-storage machine of claim 1 wherein determining whether the human subject is complying with or deviating from the rule is further based on audio data acquired in the environment.

6. The instruction-storage machine of claim 1 wherein the human subject is one of a plurality of human subjects in the environment, and wherein the rule does not apply to another human subject in the environment.

7. The instruction-storage machine of claim 1 wherein the rule is a health rule pertaining to the health of the human subject, or a safety rule pertaining to personal safety in the environment, or a security rule pertaining to security in the environment.

8. The instruction-storage machine of claim 1 wherein issuing the notification includes issuing one or more of a text transmission, an image transmission, an audio transmission, and a video transmission.

9. The instruction-storage machine of claim 1 wherein the computed aspect includes a location of the human subject on a coordinate system.

10. The instruction-storage machine of claim 1 wherein the human subject is first among a plurality of human subjects found in the depth data, and wherein the computed aspect includes the location of the first human subject relative to the other found human subjects.

11. The instruction-storage machine of claim 1 wherein the computed aspect includes a characterization of a size or shape of one or more physical features of the human subject.

12. The machine of claim 1 wherein the computed aspect includes an identity of the human subject determined from among a plurality of candidate human subjects.

13. The instruction-storage machine of claim 1 wherein the computed aspect includes a posture or gestural change in the posture of the human subject.

14. The instruction-storage machine of claim 1 wherein the computed aspect includes an action of the human subject as defined by a series of gestural changes in a posture of the human subject.

15. The instruction-storage machine of claim 1 wherein the computed aspect includes a behavior pattern of the human subject as defined by a series of actions of the human subject, the actions defined by a series of gestural changes in a posture of the human subject.

16. The instruction-storage machine of claim 1 wherein the computed aspect includes a heart rate and/or respiration rate of the human subject.

17. The instruction-storage machine of claim 1 wherein the aspect is computed further based on audio or speech data sensed in the environment.

18. An instruction-storage machine holding instructions that, when executed by a logic machine, cause the logic machine to:

find a human subject in depth data acquired with one or more depth cameras arranged to image an environment;

compute an aspect of the human subject from the depth data;

identify a trend based on the computed aspect; and

report the identified trend.

19. The instruction-storage machine of claim 18 wherein the trend is a trend in a behavior of the human subject observed in the depth data over a period of time.

20. An instruction-storage machine holding instructions that, when executed by a logic machine, cause the logic machine to:

find a human subject in depth data acquired with a plurality of depth cameras, each depth camera providing a different field of view of an environment;

track the human subject from the field of view of one depth camera to the field of view of another depth camera;

compute a virtual skeleton based on the depth data to model the human subject;

analyze a movement of the virtual skeleton to determine whether the human subject is complying with or deviating from a rule; and

issue a notification if the human subject is deviating from the rule.