Methods and apparatus to monitor environments

• US 9,020,189 B2
• Filed: 12/07/2012
• Issued: 04/28/2015
• 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, Alex
• Primary Examiner(s): TSAI, TSUNG YIN
• Application Number:
  US13/708,698
• Publication Number:
  US 20140161305A1
• Time in Patent Office: 872 Days
• Field of Search: None
• US Class Current: 382/103
• 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 a plurality of three-dimensional data points having respective depth values representative of distances between a sensor and respective objects of an environment; when a first set of the three-dimensional data points has a first depth value less than a threshold, executing 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 greater than the threshold, executing 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 tangible machine readable storage medium comprising instructions that, when executed, cause a machine to at least:

execute, in connection with a first frame of data, a three-dimensional recognition analysis on an object detected in an environment within a threshold distance from a sensor;

store a location of the object; and

in response to detecting that the first object has moved outside the threshold distance from the sensor in connection with a second frame subsequent to the first frame;

execute a two-dimensional recognition analysis on the object in the second frame; and

use the stored location of the object as a focal point for the two-dimensional analysis.

2. A storage medium as defined in claim 1, wherein the instructions, when executed, cause the machine to use the stored location of the object as the focal point for the two-dimensional recognition analysis by limiting the two-dimensional recognition analysis to a portion of the second frame associated with the stored location of the object in the first frame.

3. A storage medium as defined in claim 1, wherein the instructions, when executed, cause the machine to use the stored location of the object as the focal point for the two-dimensional recognition analysis by limiting the two-dimensional recognition analysis to a portion of the second frame corresponding to a shape and surrounding the stored location of the object in the frame.

4. A storage medium as defined in claim 1, wherein the instructions, when executed, cause the machine to store the location of the object by recording a two-dimensional coordinate in association with the first frame.

5. A storage medium as defined in claim 1, wherein the instructions, when executed, cause the machine to analyze captured three-dimensional data of the environment to determine whether the object is within the threshold distance from the sensor.

6. A storage medium as defined in claim 1, wherein the instructions, when executed, cause the machine to execute the two-dimensional recognition analysis in response to occurrence of a time event.

7. A storage medium as defined in claim 1, wherein the three-dimensional and the two-dimensional recognition analyses determine whether the respective objects of the environment correspond to people.

8. A storage medium as defined in claim 7, wherein the instructions, when executed, cause the machine to calculate a people count using results of at least one of the three-dimensional or the two-dimensional recognition analyses.

9. An audience measurement device, comprising:

a first data analyzer to execute a first recognition analysis on three-dimensional data representative of a first object within a threshold distance from a three-dimensional sensor;

a second data analyzer to execute a second recognition analysis on two-dimensional data representative of a second object outside the threshold distance from the three-dimensional sensor; and

a counter to combine a first detection of a first person provided by the first data analyzer and a second detection of a second person provided by the second data analyzer to generate a people count for an environment, wherein at least one of the first data analyzer, the second data analyzer or the counter is implemented via a logic circuit.

10. An apparatus as defined in claim 9, further comprising a crossover detector to detect the first person travelling from within the threshold distance to outside the threshold distance, the crossover detector to record a location of the first person when the first person travelled outside the threshold distance.

11. An apparatus as defined in claim 10, further comprising a limiter to focus the second recognition analysis on the location of the first person.

12. An apparatus as defined in claim 11, wherein the limiter is to define a boundary within the two-dimensional data in which to perform the second recognition analysis to areas adjacent to the location of the first person.

13. An apparatus as defined in claim 12, wherein a shape of the boundary to be defined by the limiter depends on a type of body part detected by the first data analyzer.

14. A method comprising:

executing, via a processor, in connection with a first frame of data, a three-dimensional recognition analysis on an object detected in an environment within a threshold distance from a sensor;

storing a location of the object; and

in response to detecting that the first object has moved outside the threshold distance from the sensor in a second frame subsequent to the first frame;

executing, via the processor, a two-dimensional recognition analysis on the object in the second frame; and

using the stored location of the object as a focal point for the two-dimensional analysis.

15. A method as defined in claim 14, wherein the using of the stored location of the object as the focal point for the two-dimensional recognition analysis comprises limiting the two-dimensional recognition analysis to a portion of the second frame associated with the stored location of the object in the first frame.

16. A method as defined in claim 14, wherein the using of the stored location of the object as the focal point for the two-dimensional recognition analysis comprises limiting the two-dimensional recognition analysis to a portion of the second frame corresponding to a shape and surrounding the stored location of the object in the frame.

17. A method as defined in claim 14, wherein the storing of the location of the object comprises recording a two-dimensional coordinate in association with the first frame.

18. A method as defined in claim 14, further comprising analyzing captured three-dimensional data of the environment to determine whether the object is within the threshold distance from the sensor.

19. A method as defined in claim 14, wherein the executing of the two-dimensional recognition analysis is in response to occurrence of a time event.

20. A method as defined in claim 14, wherein the three-dimensional and the two-dimensional recognition analyses determine whether the respective objects environment correspond to people.

21. A method as defined in claim 20, further comprising calculating a people count using results of at least one of the three-dimensional or the two-dimensional recognition analyses.