Methods and apparatus to monitor environments

• US 9,529,451 B2
• Filed: 03/26/2015
• Issued: 12/27/2016
• Est. Priority Date: 12/07/2012
• Status: Active Grant

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Lee, Morris, Terrazas, Alejandro
• Primary Examiner(s): TSAI, TSUNG YIN
• Application Number:
  US14/669,798
• Publication Number:
  US 20150199032A1
• Time in Patent Office: 642 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G01B 11/254 Projection of a pattern, viewing through a pattern, e.g. moiré
• CPC Class Codes: G06F 3/0304 Detection arrangements using opto-electronic means constructional details of pointing devices not related to the detection arrangement using opto-electronic means G06F3/033; optical digitisers G06F3/042
• CPC Class Codes: G06T 7/593 from stereo images
• CPC Class Codes: G06V 10/145 Illumination specially adapted for pattern recognition, e.g. using gratings
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: H04H 60/66 for using the result on distributors' side
• CPC Class Codes: H04N 13/261 with monoscopic-to-stereoscopic image conversion
• CPC Class Codes: H04N 21/44218 Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV program methods or arrangements for recognising human body or animal bodies or body parts G06V40/10; methods or arrangements for acquiring or recognising human faces, facial parts, facial sketches, facial expressions G06V40/16; methods or arrangements for recognising movements or behaviour G06V40/20; arrangements for identifying users in broadcast systems H04H60/45

Abstract

Methods and apparatus to monitor environments are disclosed. An example method includes analyzing, with a processor, a plurality of three-dimensional data points having respective depth values representative of distances from a sensor of an environment; when a first set of the three-dimensional data points has a first depth value satisfying a threshold, executing, with the processor, a first type of recognition analysis on a first area of the environment corresponding to the first set of the three-dimensional data points; and when a second set of the three-dimensional data points has a second depth value not satisfying the threshold, executing, with the processor, a second type of recognition analysis different than the first type of recognition analysis on a second area of the environment corresponding to the second set of the three-dimensional data points.

Claims

1. A method, comprising:

analyzing, by executing an instruction with a processor, a plurality of three-dimensional data points having respective depth values representative of distances from a sensor of an environment;

when a first set of the three-dimensional data points has a first depth value satisfying a threshold, executing, by executing an instruction with the processor, a three-dimensional recognition analysis on a first area of the environment corresponding to the first set of the three-dimensional data points; and

when a second set of the three-dimensional data points has a second depth value not satisfying the threshold, executing, by executing an instruction with the processor, a two-dimensional recognition analysis on a second area of the environment corresponding to a first set of two-dimensional data points representative of at least a portion of the environment corresponding to the second set of three-dimensional data points.

2. The method as defined in claim 1, wherein the three-dimensional data points are captured via a depth sensor using electromagnetic beams projected in a pattern, and the two-dimensional data points are captured via a camera.

3. The method as defined in claim 1, further including storing a two-dimensional coordinate of the first set of the three-dimensional data points in association with a first frame.

4. The method as defined in claim 3, further including using the two-dimensional coordinate to focus the two-dimensional recognition analysis on the first area of the environment for a second frame subsequent to the first frame.

5. The method as defined in claim 1, further including triggering execution of the two-dimensional recognition analysis in response to elapsing of a time interval.

6. The method as defined in claim 1, wherein the first three-dimensional and two-dimensional recognition analyses determine whether an object of the environment corresponds to a person, and further including calculating a people count using results of the at least one of the three dimensional or two dimensional recognition analyses.

7. A tangible machine readable storage medium comprising instructions that, when executed, cause a machine to at least:

analyze a plurality of three-dimensional data points having respective depth values representative of distances from a sensor of an environment;

when a first set of the three-dimensional data points has a first depth value satisfying a threshold, execute a three-dimensional recognition analysis on a first area of the environment corresponding to the first set of the three-dimensional data points; and

when a second set of the three-dimensional data points has a second depth value not satisfying the threshold, execute a two-dimensional recognition analysis on a second area of the environment corresponding to a first set of two-dimensional data points representative of at least a portion of the environment corresponding to the second set of three-dimensional data points.

8. The storage medium as defined in claim 7, wherein the three-dimensional data points are captured via a depth sensor using electromagnetic beams projected in a pattern, and the two-dimensional data points are captured via a camera.

9. The storage medium as defined in claim 7, wherein the instructions, when executed, cause the machine to store a two-dimensional coordinate of the first set of the three-dimensional data points in association with a first frame.

10. The storage medium as defined in claim 9, wherein the instructions, when executed, cause the machine to use the two-dimensional coordinate to focus the two-dimensional recognition analysis on the first area of the environment for a second frame subsequent to the first frame.

11. The storage medium as defined in claim 7, wherein the instructions, when executed, cause the machine to trigger execution of the two-dimensional recognition analysis in response to elapsing of a time interval.

12. The storage medium as defined in claim 7, wherein the three-dimensional and two-dimensional recognition analyses determine whether an object of the environment corresponds to a person, and the instructions, when executed, cause the machine to calculate a people count using results of the at least one of the three-dimensional or two-dimensional of recognition analyses.

13. An audience measurement device, comprising:

a depth filter to analyze a plurality of three-dimensional data points having respective depth values representative of distances from a sensor of an environment;

a first data analyzer to, when the depth filter determines that a first set of the three-dimensional data points has a first depth value satisfying a threshold, execute a three-dimensional recognition analysis on a first area of the environment corresponding to the first set of the three-dimensional data points;

a second data analyzer to, when a second set of the three-dimensional data points has a second depth value not satisfying the threshold, execute a two-dimensional recognition analysis on a second area of the environment corresponding to a first set of two-dimensional data points representative of at least a portion of the environment corresponding to the second set of three-dimensional data points, at least one of the depth filter, the first data analyzer, or the second data analyzer implemented via a logic circuit.

14. The audience measurement device as defined in claim 13, further including a depth sensor to capture the three-dimensional data points using electromagnetic beams projected in a pattern, and a camera to capture the two-dimensional data points.

15. The audience measurement device as defined in claim 13, wherein the second data analyzer is to use a two-dimensional coordinate of the first set in a first frame to focus the two-dimensional recognition analysis on the first area of the environment for a second frame subsequent to the first frame.

16. The audience measurement device as defined in claim 13, further including a trigger to trigger the second data analyzer to execute the two-dimensional recognition analysis in response to elapsing of a time interval.

17. The audience measurement device as defined in claim 13, wherein the first and second data analyzers are to determine whether an object of the environment corresponds to a person, and further including a body counter to calculate a people count using results of the at least one of the first three-dimensional or two-dimensional recognition analyses.