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FACIAL VERIFICATION linked to a PIN Code
 
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Face Recognition user manual

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Face Recognition
       Value Proposition 
  

 

                             

Provide all face recognition requirements;

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-System comes with everything required to capture, save, create databases of faces, and compare facial images;
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-Free loading of client database of images;
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-Customized system for distributor;
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-Low cost, differentiate on customer service

 

Face Recognition
          SYSTEM DESCRIPTION
 

Use face recognition to assist in identification.

Manually compare live & saved facial images against a database of saved face images, with an operator reviewing results, making decision.
One is using the face recognition system to check if the person has been seen before, with the operator to check the match. 
Using Face Recognition one can IDENTIFY repeat trouble makers or banned people and take appropriate action
 

Face Recognition
                       Differences

-Internet utilisation to distribute the codes required;
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-PC support is not an issue (Dell laptop);
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-Binning  reduces database size (sex, colour, age);
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-Costing model – Distributors, being close to
                         customer, gets most benefit of sale
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-Linking various vertical markets together via web server to update each site (card counter / pick pocket / problem gambler loaded in CT , immediately distributed to all other members).
Face Recognition
                  Market Entry
Use MBA dissertation to approach the casinos and other vertical markets to promote the purchase of face recognition.
New National Gambling Bill introduces a system of voluntary and court-ordered exclusion of problem gamblers from casinos.  A wide range of exclusion techniques for access control could be applied to South African casinos.  However, there are no clear criteria on which to base the decision of which system is to be implemented.  Various role players to be considered to determine what can be deployable in casino applications.  
Framework, from a business perspective, is proposed which allows multiple role players and varied criteria to effectively evaluate a range of possible solutions.  Framework applied to the role players affected by the proposed exclusion of problem gamblers from gambling.  Main role players evaluated a no. of possible exclusion techniques according to a range of NB criteria.

 

 

 

 

Face Recognition
                  Typical clients

 

Casino client
Typical casino client would have a number of facial databases:
• 1 – Banned clients (Gamblers Anonymous);
• 2 – Common criminals (Police Database).
• 3 – Known card sharks (From other casinos).
 

Shopping Center or large shop, such as Gateway or Game

The security control center or surveillance room would use fixed or dome cameras to watch for in store thefts by either staff or customers. When a gang is identified need to be able to e-mail images of thieves to other shops in the area for them to be on the look out for the gang.
 

 

                Work place environment
Screen prospective employees.
Have pictures of all staff and have a database of staff who have been fired for theft and other misdemeanors.
Allows comparison of prospective employees with images of people they should not employ. 
When a person is caught stealing they let all other similar companies know not to employ that person. 

 

 

I-Cube.   All rights reserved.  Revised: February 18, 2008 .

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Police Report: Face Recognition CCTV Unreliable

By Mick Meaney
RINF Alternative News 

New tests conducted by police yet again prove an increasing number of surveillance systems are unreliable.

200 people were enrolled to test CCTV face recognition software on three systems which failed to recognise 8 out of 10 people, even when the system was fed images of people standing still - one of the easiest settings often used to suggest the software is reliable.

The tests were conducted on software produced by Cognitec, Bosch and Cross Match.

The federal police in Germany who conducted the test are citing “bad lighting” as the reason for the failure and required the test subjects to be fitted with RFID tags to help with the identification process.

The final test report rightly advises against the use of the system and suggests it only be in use with the cooperation of the person being checked by the biometrics software. Currently the researchers believe that 23 false alarms per day would be an acceptable amount if only 1 or 2 real criminals were caught per week.

Such use would erode public trust in the system and is therefore being put on hold for the moment. With the right amount of light the systems only generated 0.1 per cent of false alarms by failing to recognize 4 out of 10 people, which is thought to be an acceptable rate for police work. You can view the report in German here.

Use of such systems is massively invasive as they can automatically retrieve personal information stored on a central database within seconds.

Through the use of number plate recognition, cars fitted with mandatory RFID, schools fingerprinting, biometric passports, a European biometric database and ‘Spy Drones’ monitoring street activity, we see not only Big Brother nations emerging but the creation of an entire European Big Brother continent were all movements can be tracked and recorded.

 

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I-Cube.   All rights reserved.  Revised: February 18, 2008 .