90 percent accurate slide for face detection presentation....

1. FACE DETECTION
BY:-
HANAN

2. CONTENTS
 Introduction
 History
 Uses
 Advantages
 Disadvantages/weak points

3. TYPE :- Biometric Software
Application
 An extremely useful biometrics technology that can identify a
specific individual in a digital image by analyzing and comparing
patterns.

4. History:-
Developed in the 1960s
 The first semi-automated system for face recognition required the
administrator to locate features (such as eyes, ears, nose, and
mouth) on the photographs before it calculated distances and
ratios to a common reference point, which were then compared to
reference data.)
 Early Advancements:- In the 1970s, Goldstein, Harmon,
and Lesk1 used 21 specific subjective markers such as hair color and
lip thickness to automate the recognition.

5. PUBLIC ATTENTION :-
 The technology first captured the public’s attention from the media
reaction to a trial implementation at the January 2001 Super Bowl.
 This technology was first used to identify mug shots by capturing
surveillance images and comparing it with police database.

6. Masterminds behind
advancements.
 Back in 2001, two computer scientists, Paul Viola and
Michael Jones, triggered a revolution in the field of computer
face detection.
 Their breakthrough was an algorithm that could spot faces in an
image in real time. Indeed, the so-called Viola-Jones algorithm was
so fast and simple that it was soon built into standard point and
shoot cameras.

7. FACE DETECTION
(now a days)
Face detection now a days is fast , more
accurate and easy.

8. Yesterday and Today
20th century
 We have to locate nose,mouth
e.t.c
 Slow and less accurate.
 Can detect only one face at a
time.
 Used only by government.
21st century
 Fully automatic detection.
 Fast and accurate.
 Capable of detecting multiple
faces.
 Everybody can use.

9. Patterns. Automatic .
Single face. Multiple faces.

10. FOUR STAGES OF IDENTIFICATION
Capture-Capture the behavioral sample
Extraction-unique data is extracted from the
sample and a template is created.
Comparison-the template is compared with a
new sample.
Match/non match-the system decides whether
the new samples are matched or not.

11. SUMMARY
 The computer-based facial recognition industry has made many
useful advancements in the past decade; however, the need for
higher accuracy remains. Through the determination and
commitment of industry, government evaluations, and organized
standards bodies, growth and progress will continue, raising the bar
for face-recognition technology.
 Still working on algorithms to detect face form different angles.
(Note: The text above is taken from biometrics.gov)

12. USES OF
FACE DETECTION
BY :- WAJAHAT
MUSAB
ADEEL
HANAN

13. Uses now a days
 It is used in video surveillance, human computer interface and
image database management.


14. Is widely used in Photography
: In Photography Some recent digital cameras use face
detection for autofocus

15. . Face detection is also useful for selecting regions of interest
in photo slideshows that use a pan-and-scale Ken Burns
effect.

16. In Marketing
In Marketing Face detection is gaining the interest of marketers. A
webcam can be integrated into a television and detect any face that
walks by.
The system then calculates the race, gender, and age range of the
face.

17. In offices:
 It is used in offices now a days to mark attendance.
 Much faster way to mark attendance.

18. Law enforcement :-
 In 2001 face detection was used to identify mugshots and criminals.
 This is how it got public attention.
 Crime rate was reduced by 31% by use of this software. It compared
faces by the police data base.

19.  Face detection has make our life much easier.Now a days it is used
of goverment,military and in offices.
 It is widely used in mobiles,camera and laptops.
 It has make our life more secure by face recognition screen lock.

20. Uses in military:-
 Face detection is used in modern warfare. Most of the missile system use
face detection to identify there target.
 In Military facial recognition technology can be mounted on weapons
and other platforms and used to identify potential terrorists where
Recent trials were favourable.

21. Local uses:-
 Outdoor surveillance camera service : Face and motion detection
technology may help making a
 good service to keep you secure. Firstly, it will give you a signal of
somebody’s coming even before he rings the doorbell.

22. Summary
FACE DETECTION HAS CHANGED OUR LIFE IN MANY WAYS BUT STILL
THERE IS NEED TO MAKE BETTER ALGORITHM TO DETECT FACE FROM
MANY ANGLES.

23. Advantages of
face recognition
technology

24. Face recognition is ten times more accurate then other
biometric software like fingerprint e.t.c.

25.  It requires no physical interaction on
behalf of user
 It is accurate and allows for high
enrolment and verification
 Not require an expert to interpret the
comparison result
 Can use your existing infrastructure
 Passive identification
 Convenient, social acceptability
 More user friendly
 Inexpensive technique of
identification

26. High Success Rate
Facial biometrics technology today has a high success rate. You can
feel secure knowing that your biometrics computer security system
will be successful at tracking time and attendance while providing
better security.

27. Automated Facial System
Many companies like the fact that biometric imaging systems are
automated. You won’t have to worry about having someone there
to monitor the system 24 hours a day.

28. Better Security
You’ll also enjoy better security with a face biometrics system. Not
only can you track employees thru biometrics time attendance
tracking, but any visitors can be added to the system and tracked
throughout the area too. Anyone that is not in the system will not be
given access

29. Face recognition
(disadvantages)
IT IS NOT 100% ACCURATE.
RESEARCHER DON’T HAVE CONSISTENCY IN MAKING THIS SOFTWARE.

30. Conditions in which face
recognition does not work.
 Poor lighting
 Sunglasses
 Long hair
 Low resolution
 Other objects on face eg tattoo
 Face can be detected from front it is not applicable from left and
right.

31. Measures taken to advance face
recognition
 Canada now allows only neutral facial expressions in passport
photos.
 On 18 January 2013 Japanese researchers created a privacy visor
that uses infrared light to make the face underneath it recognizable.

32. Effectiveness
 Critics of the technology complain that the London Borough of
Newham scheme has, as of 2004, never recognized a single
criminal, despite several criminals in the system's database living in
the Borough and the system having been running for several years.
 A system in Boston’s Logan Airport was shutdown in 2003 after failing
to make any match during two year test period.
 In Birmingham about 34% in crime rate was decreased, actually the
system didn’t workout.

33. Comparing with other
Technologies.
 When we compare face recognition software with other
technologies such as biometric tech, the face recognition didn’t
give us effective result.
 It is not reliable and efficient.
 One advantage is that it doesn’t require test subject to run, when
other techs like biometric, iris scan, voice recognition needs a test
subject to run.
 In crowded areas it work better than other.