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Infrared Security System and Method
US Patent 7,738,008
June 15 2010
How Does It Work?
June 2010
IAI = Infrared Applications Inc.
Test Set-up: Visual Orientation
• Two cameras with a common surveillance
field of view.
• Camera B can be seen in Camera A’s
FOV.
• Camera A is positioned in Camera B’s
FOV
• Angles between cameras & targets are as
shown
• The Cameras are 105 feet apart.
Camera A
Camera B Location
Target
Camera B
Camera A Location
Target
ISS Geometry
R2
R1
Target Planter Location
Set up value, distance between Cameras
Cameras & target Actual Positions
Range computations, R1 & R2
Real time calculation of Target Size
• Cameras are IR calibrated and balanced
Gain & Level using common objects
• Each IR camera employs convention 2
dimensional processing.
Target segmentation
Threshold
• Two dimensional information is processed in real
time into 3 dimensional information
Precise object location (x,y,z, coordinates)
Precise physical size (sq. ft)
Threat Determination
• Targets are defined by size
– (eg: truck, car, large animal, human, small
animal/child, very small animal)
• A threat is defined as a specific target in a
defined location
• The Location
– All or part of surveillance field
– Or a specific threat area: No fly zone
Target Upgrade & Tracking
• Target was defined by actual size.
• Once classified as a threat
– Actual the actual target size is stored.
– Actual Inherent Thermal Contrast is stored.
• Threat is continuously tracked by:
– Both cameras or one camera if either camera
becomes obscured. (2 D tracking using Actual target
size for ranging and Inherent contrast for improved
discrimination)
• Continuously tracking:
– Allows higher order threat determinations
Intruder Example
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Series of snap shots of an intruder
The initial detection is by Camera A.
Then, Intruder enters Camera B FOV
The intruder enters the yard.
The intruder is continuously tracked
through partial and total camera
obscurations.
• Snap shots are 1/40 the actual number of
independent samples at video frame rates.
Camera B, initial detection
Camera A ------ Camera B
Camera A ------ Camera B
Almost fully obscured
Camera A ------ Camera B
Camera A ------ Camera B
Camera A ------ Camera B
Camera A ------ Camera B
Partially Obscured
Mostly Obscured
Intruder
• The target alarm sounded approximately 0.5
seconds after Camera B detection.
• The highly cluttered scene caused each camera
to lose the target because of complete or
partially obscurations.
• The “arc” path of the intruder causes an aspect
change with small changes in computed size.
• With more than 300 independent sampled image
pairs, the confidence level is extremely high.
• The Intruder was observed to be carrying a tool
or a weapon.
Object in Hand
Advance Discrimination Techniques
• Target Refinement:
– ITC & Size of each target allows discrimination between targets in a
multi-target environment.
• Target Image Dropout
– “Inherent thermal contrast” and actual size are used to re-acquire and
separate new targets from old target.
• Multiple targets:
– Can merge together and then separate, where ITC and physical size
assigned to each target are used to maintain the identity of each target.
• Behavioral traits
– Movement over time against a preset criteria are associated with a
certain kinds of threat.
• Redundant information
– ITC and physical size provides redundant data that support the
application of best estimate theory.
Advance Discrimination Techniques
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Designed for multiple targets, each target having a separate threat
definition, and threat response. (examples one or more)
– “People-size” targets in specific areas at defined times
– People congregating (crowd recognition)
– Loitering (excessive time)
– Stalking, (time history relationship between two targets)
– Lying in wait, (serious home evasion threat)
– A unattended child entering a swimming pool
– Animals entering controlled areas
– People exhibiting threatening behavioral
– “Man down” recognition
– Cars, time and location criteria
– Trucks, time and location criteria
– People count, matching entering with exits, tagging size
– Verification, matching size with independent data, e.g. RFID data
Summary
• Field tests have demonstrated the attributes of the
Infrared Security System.
• ISS provides reliable target detection and threat
classification.
• High level of confidence that all false alarms have been
rejected or minimized.
• ISS has the capability to be the first fully automatic
physical security system
• ISS minimizes or eliminates the costly dedicated control
rooms of TV monitors and security analysts.
• ISS provides the real time information needed by a first
responder, or Information needed by the occupants of
the home to avoid the threat.
ISS Applications
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Major Business Sectors
– Home Security (adjunct to existing home security)
– Factories (upgrade from forensic to threat negation)
– 24/7 High Value (integrated threat assessment)
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Power Plants
Refineries
Farms (man and environmental threats, seasonal threat)
Military Installations & portable field operations
Shopping Malls, parking lot security (host of threats)
Airports: intrusion, unattended luggage, & threat tracking
Green Applications
– Automobile Sales lots
– Correctional Institutions
– Transportation Depots/shipyards/docks
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Other forms employing the core patented principle of 3D processing