Multiple camera control system
A multiple camera tracking system for interfacing with an application program is provided. The tracking system includes multiple cameras arranged to provide different viewpoints of a region of interest, and are operable to produce a series of video images. A processor is operable to receive the series of video images and detect objects appearing in the region of interest. The processor executes a process to generate a background data set from the video images, generate an image data set for each received video image, compare each image data set to the background data set to produce a difference map for each image data set, detect a relative position of an object of interest within each difference map, and produce an absolute position of the object of interest from the relative positions of the object of interest and map the absolute position to a position indicator associated with the application program.
1. A method comprising:
accessing a first image and a second image of at least a portion of a scene;
analyzing, by a processor, the first image and the second image to detect an object of interest in at least one of the first image and the second image;
generating a history of the object of interest;
detecting an occurrence of a gesture made by the object of interest by analyzing the history; and
providing an output based on the detected occurrence of the gesture.
2. The method of claim 1 , further comprising:
determining coordinates representing a location of the detected object of interest, wherein:
the coordinates representing the location of the detected object of interest are used in generating the history of the object of interest.
3. The method of claim 1 , wherein analyzing the first image and the second image to detect the object of interest comprises:
generating a background model, wherein the background model comprises a luminance value for each pixel in a region of interest and the object of interest is detected within the region of interest.
4. The method of claim 3 , wherein analyzing the first image and the second image to detect the object of interest further comprises:
creating a difference map, wherein the difference map comprises positions of pixels, from at least one of the first image and the second image, having a luminance inconsistent with the background model.
5. The method of claim 4 , wherein analyzing the first image and the second image to detect the object of interest further comprises:
performing a cluster identification process on the difference map to detect the object of interest.
6. The method of claim 3 , wherein the region of interest is substantially planar.
7. The method of claim 1 , wherein providing the output based on the detected occurrence of the gesture comprises controlling an application based on the detected occurrence of the gesture.
8. The method of claim 1 , wherein the gesture comprises a poking gesture.
9. The method of claim 1 , wherein the object of interest comprises a human hand.
10. A system, comprising:
one or more processors; and
a memory communicatively coupled with and readable by the one or more processors and having stored therein processor-readable instructions which, when executed by the one or more processors, cause the one or more processors to:
access a first image and a second image of at least a portion of a scene;
analyze the first image and the second image to detect an object of interest in at least one of the first image and the second image;
generate a history of the object of interest;
detect an occurrence of a gesture made by the object of interest by analyzing the history; and
provide an output based on the detected occurrence of the gesture.
11. The system of claim 10 , wherein the processor-readable instructions further comprise processor-readable instructions which, when executed by the one or more processors, cause the one or more processors to:
determine coordinates representing a location of the detected object of interest, wherein:
the coordinates representing the location of the detected object of interest are used in generating the history of the object of interest.
12. The system of claim 10 , wherein the processor-readable instructions that cause the one or more processors to analyze the first image and the second image to detect the object of interest further comprise processor-readable instructions which, when executed by the one or more processors, cause the one or more processors to:
generate a background model, wherein the background model comprises a luminance value for each pixel in a region of interest and the object of interest is detected within the region of interest.
13. The system of claim 12 , wherein the processor-readable instructions that cause the one or more processors to analyze the first image and the second image to detect the object of interest further comprise processor-readable instructions which, when executed by the one or more processors, cause the one or more processors to:
create a difference map, wherein the difference map comprises positions of pixels, from at least one of the first image and the second image, having a luminance inconsistent with the background model.
14. The system of claim 13 , wherein the processor-readable instructions that cause the one or more processors to analyze the first image and the second image to detect the object of interest further comprise processor-readable instructions which, when executed by the one or more processors, cause the one or more processors to:
perform a cluster identification process on the difference map to detect the object of interest.
15. The system of claim 12 , wherein the region of interest is substantially planar.
16. The system of claim 10 , wherein the processor-readable instructions that cause the one or more processors to provide the output based on the detected occurrence of the gesture further comprises processor-readable instructions configured to cause the one or more processors to control an application based on the detected occurrence of the gesture.
17. The system of claim 10 , wherein the gesture comprises a poking gesture.
18. The system of claim 10 , wherein the object of interest comprises a human hand.
19. An apparatus, the apparatus comprising:
means for accessing a first image and a second image of at least a portion of a scene;
means for analyzing the first image and the second image to detect an object of interest in at least one of the first image and the second image;
means for generating a history of the object of interest;
means for detecting an occurrence of a gesture made by the object of interest by analyzing the history; and
means for providing an output based on the detected occurrence of the gesture.
20. The apparatus of claim 19 , further comprising:
means for determining coordinates representing a location of the detected object of interest, wherein:
the coordinates representing the location of the detected object of interest are used in generating the history of the object of interest.
21. The apparatus of claim 19 , wherein the means for analyzing the first image and the second image to detect the object of interest comprises:
means for generating a background model, wherein the background model comprises a luminance value for each pixel in a region of interest and the object of interest is detected within the region of interest.
22. The apparatus of claim 21 , wherein the means for analyzing the first image and the second image to detect the object of interest further comprises:
means for creating a difference map, wherein the difference map comprises positions of pixels, from at least one of the first image and the second image, having a luminance inconsistent with the background model.
23. The apparatus of claim 22 , wherein the means for analyzing the first image and the second image to detect the object of interest further comprises:
means for performing a cluster identification process on the difference map to detect the object of interest.
24. A computer program product residing on a non-transitory processor-readable medium, the computer program product comprising processor-readable instructions configured to cause one or more processors to:
access a first image and a second image of at least a portion of a scene;
analyze the first image and the second image to detect an object of interest in at least one of the first image and the second image;
generate a history of the object of interest;
detect an occurrence of a gesture made by the object of interest by analyzing the history; and
provide an output based on the detected occurrence of the gesture.