Infrared intrusion detection system (IRIDS)

1. A system for intrusion detection comprising:

an imager directed towards an object in an interior space; the imager in data communication with a computer;

the computer configured to:

process digital three-dimensional image data received from the imager; execute a change detection algorithm in response to the processed three-dimensional data to determine movement of the object; and generate an output signal in response to detecting movement of the object above a predetermined threshold;

wherein the change detection algorithm comprises a first phase and a second phase; the first phase configured to gather a base-line data, and the second phase to detect an alarm condition; the first phase configured to continually approximate a depth of each pixel on a sensor using an exponential smoothing approach; and to calculate a maximum deviation of the respective frame from this exponentially smoothed depth measurement; and generate an estimated convolved error between a scene movement and noise within the sensor associated with a respective pixel.

2. The system of claim 1 , wherein the imager is configured to generate a range map.

3. The system of claim 1 , wherein the change detection algorithm comprises a smoothing function.

4. The system of claim 1 , wherein the change detection algorithm determines whether a movement sensed by imager meets a predetermined criteria for generating an alarm signaling an intrusion through the object, wherein the object is a monitored door.

5. The system of claim 1 , wherein the imager receives the three-dimensional image data in response to signals generated in the imager and directed at the object.

6. The system of claim 1 , wherein the three-dimensional image data comprises a three-dimensional point cloud and wherein the imager generates an infrared range map in response to the three-dimensional point cloud data.

7. The system of claim 5 , wherein the imager is configured to generate an infrared range map based on Time of Flight (TOF) data.

8. The system of claim 7 , wherein the imager applies change detection in response to the infrared range map to create a volumetric sensor.

9. The system of claim 7 , wherein the infrared range map is based on thousands of IR spots projected by the imager.

10. The system of claim 1 , wherein the imager further comprises a laser and a multifaceted lens.

11. The system of claim 10 , wherein the Time of Flight (TOF) measurements are made by integrating light pulse to create a 3-dimensional range map.

12. The system of claim 1 , wherein the imager communicates with the computer via data link.

13. The system of claim 1 , wherein the computer comprises an Intel model NUC© small form-factor x86 computer with solid-state hard-drives.

14. The system of claim 1 , wherein the imager is mounted in the secure area with a line of sight directed to the object.

15. The system of claim 1 , wherein a detection envelope generated by the imager is bound by a field of view (FOV) of the imager, and wherein the imager provides a horizontal FOV equal to about 70° and a vertical FOV equal to about 60°.

16. The system of claim 1 , wherein the imager further comprises a depth resolution of about 1 mm ( 1/25″) and a spatial resolution of about 24 mm 2 per pixel at a range of 4.57 m.

17. The system of claim 1 , wherein the wherein the imager further comprises an infrared camera.

18. The system of claim 1 , wherein the IR camera provides a 512×424 pixel resolution and sampling rate of 30 frames per second; and provides about 6.5 million pixels per second.

19. A method of intrusion detection comprising:

providing an imager directed towards an object in an interior space;

receiving Time of Flight signals by the imager;

processing digital three-dimensional image data received from the imager; and

executing a change detection algorithm in response to the processed three-dimensional data to determine movement of the object;

wherein the change detection algorithm comprises a first phase and a second phase; the first phase configured to gather a base-line data, and the second phase to detect an alarm condition; the first phase configured to continually approximate a depth of each pixel on a sensor using an exponential smoothing approach; and to calculate a maximum deviation of the respective frame from this exponentially smoothed depth measurement; and generate an estimated convolved error between a scene movement and noise within the sensor associated with a respective pixel.

20. A system for intrusion detection comprising:

an imager directed towards an object in an interior space; the imager in data communication with a computer;

the computer configured to:

process digital three-dimensional image data received from the imager; execute a change detection algorithm in response to the processed three-dimensional data to determine movement of the object; and generate an output signal in response to detecting movement of the object above a predetermined threshold;

wherein the change detection algorithm comprises a first phase and a second phase; the first phase configured to gather a base-line data, and the second phase to detect an alarm condition; the first phase configured to continually approximate a depth of each pixel on a sensor using an exponential smoothing approach; and to calculate a maximum deviation of the respective frame from this exponentially smoothed depth measurement; and generate an estimated convolved error between a scene movement and noise within the sensor associated with a respective pixel;

and wherein, in response to determining that the sensor has gathered a predetermined set of data, transition to the second phase; the second phase configured to determine a difference between a measured depth of a respective pixel and a depth of a respective base-line pixel data; and in response to the determined depth differential being greater than a perceived error during base-line-gathering, accumulate a bias towards an alarm state; and after the respective pixel exceeds a predetermined bias, generate an alarm signal.