METHODS AND APPARATUS TO MONITOR ENVIRONMENTS

• US 20140161305A1
• Filed: 12/07/2012
• Published: 06/12/2014
• 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
• Granted Patent: US 9,020,189 B2
• Time in Patent Office: Days
• 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 method, comprising:

analyzing, with a processor, 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, 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 greater than 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.

2. A method as defined in claim 1, wherein the first type of recognition analysis analyzes the three-dimensional data points in the first set, and the second type of recognition analysis analyzes a third set of two-dimensional data representative of at least a portion of the environment.

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

4. A method as defined in claim 1, further comprising storing a two-dimensional coordinate of the first set in association with a first frame.

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

6. A method as defined in claim 1, further comprising triggering execution of the second recognition analysis in response to elapsing of a time interval.

7. A method as defined in claim 1, wherein the first and second types of recognition analyses determine whether the respective objects of the environment correspond to people, and further comprising calculating a people count using results of the at least one of the first or second types of recognition analyses.

8. 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.

9. A storage medium as defined in claim 8, wherein the instructions 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.

10. A storage medium as defined in claim 8, wherein the instructions 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.

11. A storage medium as defined in claim 8, wherein the instructions cause the machine to store the location of the object by recording a two-dimensional coordinate in association with the first frame.

12. A storage medium as defined in claim 8, wherein the instructions cause the machine to analyze three-dimensional data captured of the environment to determine whether the object is within the threshold distance from the sensor.

13. A storage medium as defined in claim 8, wherein the instructions cause the machine to execute the two-dimensional recognition analysis on the environment in response to occurrence of a time event.

14. A storage medium as defined in claim 8, wherein the three-dimensional and the two-dimensional recognition analyses determine whether the respective objects of the environment correspond to people.

15. A storage medium as defined in claim 14, wherein the instructions cause the machine to calculate a people count using results of at least one of the three-dimensional or the two-dimensional recognition analyses.

16. 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 the 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.

17. An apparatus as defined in claim 16, 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.

18. An apparatus as defined in claim 17, further comprising a limiter to focus the second recognition analysis on the location of the first person.

19. An apparatus as defined in claim 18, 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.

20. An apparatus as defined in claim 19, 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.