Automated Personal Identity Recognition Using Face Detection: Spin Out OmniPerception
Submitting Institution
University of SurreyUnit of Assessment
Electrical and Electronic Engineering, Metallurgy and MaterialsSummary Impact Type
TechnologicalResearch Subject Area(s)
Information and Computing Sciences: Artificial Intelligence and Image Processing, Computation Theory and Mathematics, Information Systems
Summary of the impact
Research in biometrics carried out at Surrey since 1995 has generated IP
relating to a number of
aspects of automatic face recognition, which resulted in significant
performance improvement,
rendering this biometric technology commercially exploitable.
The advances made at Surrey include illumination invariant imaging, face
detection/localisation
using robust correlation, innovative face skin texture representation
using a multiscale local binary
pattern descriptor, a patented (and exceptionally compact) person specific
discriminant analysis,
facial component based matching, and patented multi-algorithmic fusion.
Through an IP agreement, these innovations have been commercially
exploited by the University
spinout company OmniPerception, which has developed products for various
security applications.
Underpinning research
Research in face biometrics carried out at Surrey (and led by Professor
Kittler) since 1995 has
generated Intellectual Property relating to a number of aspects of the
automatic face recognition
process, which resulted in significant performance improvement in face
recognition, rendering this
biometric technology commercially exploitable. The advances made at Surrey
include multispectral
imaging and photometric normalisation to achieve illumination invariance
[6], robust face detection
and localisation using robust correlation [3,4], innovative representation
of face skin texture using a
multiscale local binary descriptor [2], a unique patented person specific
discriminant analysis,
which is exceptionally compact allowing face matching on a smart card [6],
facial component based
matching enhancing robustness to face localisation errors [5],[6], and
multi-algorithmic fusion,
exploiting a patented error correcting decision making approach [1].
The innovative method of face image representation and matching [6]
invented by Professor Kittler
in 2000, which is now protected by a European patent, has unique
properties. Its low
computational complexity opened, for the first time, the possibility of
implementing face verification
systems on a small computing platform, such as a smart card. This
contrasts with previous
solutions with computational complexity of 2-3 orders of magnitude
greater. In parallel, a multi-classifier
system based on the concept of error correcting coding was developed at
Surrey by
Kittler, Ghaderi and Windeatt, for face recognition scenarios where
computing power was not a
constraining factor. The work was published [1] after filing for
protection in 2001 [6]. It has the
capacity to enhance face recognition performance by a factor of two.
The intellectual property encompassed by the two patents was transferred
to a university spin out
company, OmniPerception Ltd. The technology transfer to OmniPerception Ltd
was aided first by a
KTP project KTP000982-A01 during the period 2005-2007. Further
enhancements, involving 3D
face model technology developed with the support from EPSRC Research Grant
GR/S46543/01,
entitled 2D+3D=ID, were transferred to OmniPerception with the financial
assistance from a TSB
Project K1533:' Visualisation tools for effective face matching' during
2007-2009, all projects
headed by Professor Kittler. In addition, applied research carried out at
Surrey after the spin out in
2002, resulted in significant enhancements of face detection [4] and face
localisation [3] methods.
The former is achieved using a novel correlation method, which is robust
to outliers (image
degradation). The latter has been developed to perform face localisation
in general conditions
where the pose of the face image deviates from the frontal.
Another key contribution was the work on skin texture representation,
carried out at Surrey in
2005-2007. the work, which was supported by EPSRC Project GR/S98528/01 and
EU Network of
Excellence in biometrics "BIOSECURE", resulted in a powerful innovative
face descriptor based on
the Local Binary Pattern operator. The proposed multiscale generalisation
enhanced the
performance of face recognition significantly.
References to the research
1. J Kittler, R Ghaderi, T Windeatt, and J Matas. Face
verification using error correcting output
codes. Image and Vision Computing, 21:1163-1169, December 2003
3. M Hamouz, J Kittler, J-K Kamarainen, P Paalanen and J Matas,
Feature based affine-invariant
localisation of faces, IEEE Transactions on Pattern Analysis and Machine
Intelligence, pp1490-1495, vol. 27, 2005.
4. AJ Fitch, A Kadyrov, WJ Christmas and J Kittler, Fast robust
correlation, IEEE Transactions
on Image Processing, pp 1063-1073, vol. 14, 2005
5. T-K Kim and J Kittler, Locally linear discriminant analysis for
multimodally distributed classes
for face recognition with a single model image, IEEE Transactions on
Pattern Analysis and
Machine Intelligence, pp318-327, vol. 27, 2005
6. http://www.omniperception.com/about-us/technology/technology-patents-ip/
Details of the impact
The promise of the Intellectual Property in face biometrics generated by
Professor Kittler in the late
1990's, and filed for protection by Surrey at the turn of the millennium,
was instrumental in setting
up a unique commercialization framework.
This IP was vested in a University spinout company, OmniPerception Ltd,
in 2001. The spinout
company was initially assisted both, financially, from the University seed
fund and Cascade fund,
and intellectually, on a long-term basis, by the University committing any
pipeline IP, to be
generated by Professor Kittler after OmniPerception had been formed, for
the benefit of the
company. The relationship between the University and the company mirrored
the business and
exploitation model used by the Stanford University in setting up the
speech recognition company
Nuance at about the same time.
The output of the applied research in biometrics carried out at the
University of Surrey after the
formation of the company with EPSRC and EU support, jointly with
government assisted
technology transfer programmes including SMART, KTP, and DTI Technology
(TSB) projects, had
generated innovative core face biometrics technology that attracted a
Venture Capital investment
of more than £2 million to enable product development and engineering. In
2009, the production of
the OmniPerception technology was accelerated by a major investment from
BAe Systems via its
Investment in Innovation (I3) Programme, with a part of the funding
(£250k) subcontracted back to
the University to develop solutions for cross spectral face matching and
pose invariant face
recognition.
The software engineering and product development have been facilitated by
the use of common
open source image processing library RAVL. This ensured that common
classes and structures
were used for algorithm development. In April 2012 the company merged with
Visimetrics, a major
UK biometrics technology integrator, to create an enterprise with the
combined capability to
manufacture high technology products, and to integrate them in advanced
security applications.
In 2013 Visimetrics was acquired by Digital Barriers, a fast growing SME
in Homeland Security
with then more than 200 employees. A number of University of Surrey PhD
graduates have joined
the company.
The series of products that have been launched by OmniPerception since
2008 includes:
-
Face biometric access control systems CheckPoint and
CheckPoint.S. Both use illumination
invariant imaging technology (enhanced by photometric normalization),
and the multiscale
Local Binary Pattern representation coupled with facial component based
matching. The former
system requires user cooperation. It is deployed for access control to
data centres in banks,
and by Menzies to enhance security at UK airports to control access to
the air-side by cargo
handling staff. The latter version, launched only in 2011 captures and
processes face image on
the move, without the subject's awareness. This is important for
watchlist applications as
diverse as those enhancing national security, as well as crime
prevention in shopping malls
and player exclusion in casinos.
-
Face search engine Collossus allows a rapid matching of an
input face with a huge database
of faces for retrieval purposes or for recognition. The search engine
uses the basic face
technology modules, including face detection and localisation,
photometric normalisation, skin
texture representation, and discriminative face matching, with
multi-algorithm search solutions
available as options. The search engine is used by the UK Police Forces
to identify suspects,
by United Nations, and as a core subsystem in stand alone biometric
access control solutions
(e.g. time and attendance).
In April 2012 OmniPerception Ltd merged with Visimetrics, an integrator,
to create a company of
greater critical mass, with enhanced access to security markets. The
annual turnover of the new
company was in excess of £3 million and is growing. With the proven track
record of its security
product installation at the Heathrow airport, the most recent successes of
the company include the
introduction of the OmniPerception face access control systems to
Manchester and other UK
airports by Menzies.
Quoting VP IT Operations and Communications, Menzies Aviation plc
"We analysed numerous biometric technologies and suppliers back in
2009 and concluded
that OmniPerception both as a technology and organisation fitted in with
the Menzies
Aviation philosophy."
Sources to corroborate the impact
C1. CEO of OmniPerception. Contact details provided.
C2. OmniPerception
http://www.omniperception.com
http://www.omniperception.com/about-us/technology/
http://www.omniperception.com/about-us/case-studies/access-control-
airport-cargo/
Examples of product sales and installations include:
C3. Facial capture and search engine for police custody suits to
facilitate law enforcement
http://www.omniperception.com/markets/law-enforcement/
C4. Suspect identification (UK Police Forces)
http://www.omniperception.com/about-us/case-studies/case-studies-secure-facial-control/
C5. Access control to air side in airports for personnel handling
air cargo (e.g. Heathrow,
Manchester)
http://www.omniperception.com/about-us/case-studies/access-control-airport-cargo/
C6. Secure access to data centres in financial institutions
http://www.omniperception.com/about-us/case-studies/case-studies-secure-facial-control/
http://www.omniperception.com/news/2013/01/07/digital-barriers-acquires-OmniPerception/