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Creating solutions with the FaceIt Face Recognition Software Development SDK gives integrators and developers an edge in today’s fast and evolving marketplace.
By combining traditional facial geometry techniques with skin biometrics, FaceIt technology has reached exceptional levels of performance, bringing it on par with fingerprint technology for one-to-one matching and leapfrogging previous one-to-many matching results by as much as thirty percent.
With all the tools that you need to build face recognition solutions for enrollment and one-to-one and one-to-many matching, the integration process is fast and easy. The FaceIt Face Recognition Software Development SDK contains modules for face finding, template creation, quality analysis, and watchlist searches packaged in a simple C application programming interface (API).
 Features:
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Supports face finding, quality analysis, template creation, verification, identification, and watch list searches.
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Media Processing Library: Two modules that allow processing of still and live images for facial matching.
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Specifications - FaceIt Face Recognition Software Development SDK |
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Platforms Supported |
Microsoft Windows ME, 2000, XP, 2003.
Available for UNIX and Linux through
special requests.
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Input Formats |
JPEG, JPEG 2000, BMP, GIF, DirectShow,
Video For Windows. Also accepts artist
rendered images.
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Output Formats |
FaceIt G6 template and
standards-compliant facial images in
JPEG, JPEG ROI (Region of Interest),
JPEG 2000
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Faceprint Size |
VFA template - 648
bytes. LFA template - 5K
bytes. STA template - 7K
bytes.
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Recognition Matching |
Supports both
Verification (1:1) and
Identification (1:N)
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Speed |
Head Finding:
50-300 milliseconds
depending on scene
complexity.
One-to-one matching:
<1 second
One-to-many matching:
Up to 60 million per
minute CPU for vector
template depending on
hardware; when using all
3 templates, aggregate
search speed up to 10
million per minute per
CPU, depending on
hardware.
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Database Size |
Technology can support
an unlimited number of
records |
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Motion |
Detects moving as well
as stationary faces |
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Pose |
Technology works
optimally when matching
frontal images.
Face-finding detects
faces as long as both
eyes are visible.
Recognition is not
significantly affected
by variations in pose up
to 15 degrees. From 15
to 35 degrees there is a
slight loss in matching
ability. Beyond 35
degrees more significant
loss of matching may
occur.
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Race and Gender |
Performs well on all
races and both genders. |
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Robustness to
Variability |
The algorithm focuses on
the inner region of the
face and had built-in
mechanisms that
compensate for natural
variability in the face.
The result is an engine
that is robust with
respect to changes in
lighting conditions,
expression, facial hair,
and hairstyle.
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Eyeglasses |
Explicit designed to
match faces with or
without eyeglasses, as
long as the eyes are
visible and not occluded
by glare.
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Lighting |
Optimal performance is
obtained in diffuse
ambient lighting, where
the face is evenly
illuminated, without
shadows or glare. Gain
control on cameras can
be used to compensate
for back-lighting of the
face, but cameras can be
tricked by excessively
bright or dark
backgrounds into
producing images with
overly dark or light
faces. An evenness of
the lighting in the
field of view produces
the best results most
easily.
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Background |
Finds the faces in an
image against any
background, plain or
cluttered.
Recognition performance
uses only features on
the face, so it is
unaffected by the
background once the face
is successfully located.
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Image Depth and
Resolution |
Minimum of 320x240
resolution for desktop
verification and 640x480
resolution for
surveillance. Minimum of
8 bits of grayscale
depth. Recommended image
format is JPEG with
24-bit color depth and a
maximum compression of
15:1.
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Standards |
Support for CBEFF Patron
Formats A, C (BioAPI)
and D (ICAO) with both
ISO and ANSI data
interchange files
provided by FaceIt
Quality Assessment SDK
with Standards
Formatting Module.
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System Requirements:
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Three source-code sample applications that demonstrate image capture, verification (1:1 matching) and identification (1:N searching).
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Technology in simple C API for compatibility with Microsoft C and C++. Compatible with Microsoft Video for
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Windows (VfW) and DirectShow capture systems. Supports standard .jpeg, .jpeg2000, .tiff, .gif files, and frame capture from .avi and .mpeg files.
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SDK purchase includes free hot-fixes, service pack and minor point updates. Run time licenses at additional cost depending on application.
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FaceIt Face Recognition - 
