VeriLook SDK - Extended Edition

Face identification for PC and Web solutions

Click Here to download the full VeriFinger SDK brochure as a .pdf document

VeriLook facial identification technology is intended for biometric systems developers and integrators. The technology assures system performance and reliability with live face detection, simultaneous multiple face recognition and fast face matching in 1-to-1 and 1-to-many modes.

VeriLook is available as a software development kit that allows development of PC- and Web-based solutions on Microsoft Windows, Linux and Mac OS X platforms.

Advantages of VeriLook

• More than a million algorithm deployments worldwide.
• Live face detection prevents cheating with a photo in front of a camera.
• Simultaneous multiple face processing in live video and still images.
• Webcams or other low cost cameras are suitable for obtaining face images.
• Available as multiplatform SDK that supports multiple programming languages.
• Surveillance SDK is available for integrating face identification into surveillance systems.
• Reasonable prices, flexible licensing and free customer support.

VeriLook Technology and SDK

VeriLook 5.0 Standard and Extended SDK. VeriLook 5.0 Standard SDK is intended for PC-based biometric application development and the Extended SDK is suitable for developing Web-based biometric systems. Camera management software in the SDK allows simultaneous capture from multiple cameras … Read more System requirements. VeriLook-based software can be run on computers with x86 or PowerPC processors (at least 2 GHz processor recommended). Windows, Linux and Mac OS X platforms are supported. A webcam is enough to capture face images… Read more Technical specifications. VeriLook matches up to 440,000 faces per second, can enroll a face in less than 0.06 seconds, can use as little as 4 kilobytes for a face template in a database… Read more Reliability and performance tests. VeriLook algorithm has been tested with FRGC database. Experiment 1 and Experiment 2 were performed according to FRGC protocol… Read more	Click to zoom
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Download. VeriLook brochure, algorithm demo application and VeriLook 30 Day Trial SDK are available for downloading. References. More than a million copies of VeriLook are used worldwide. Case studies show the most notable projects like VeriLook being used in Lenovo notebook computers.  If you would like product references or case studies please contact us today

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Contents of VeriLook Standard SDK and Extended SDK

VeriLook SDK is based on VeriLook PC-based face recognition technology and is intended for biometric systems developers and integrators. The SDK allows rapid development of biometric applications using functions from the VeriLook algorithm that ensure fast and reliable face identification. VeriLook can be easily integrated into the customer's security system. The integrator has complete control over SDK data input and output.

VeriLook SDK includes Camera Manager library for Microsoft Windows and Linux that allows to perform simultaneous capture from multiple cameras.

VeriLook is available as the following SDKs:

• VeriLook 5.0 Standard SDK is intended for PC-based biometric application development. It includes Face Matcher and Extractor component licenses, programming samples and tutorials, camera manager library and software documentation. The SDK allows the development of biometric applications for Microsoft Windows, Linux or Mac OS X operating systems.
• VeriLook 5.0 Extended SDK is intended for biometric Web-based and network application development. It includes all features and components of the Standard SDK. Additionally, the SDK contains Face Client component licenses, sample client applications, tutorials and a ready-to-use matching server component.

The table below compares VeriLook 5.0 Standard SDK and VeriLook 5.0 Extended SDK.

VeriLook 5.0 SDK includes programming samples and tutorials that show how to use the components of the SDK to perform face template extraction or matching against other templates. The samples and tutorials are available for these programming languages and platforms:

	Windows 32 & 64 bit	Linux 32 & 64 bit	Mac OS X
Programming samples
• C/C++	+	+	+
• C#	+
• Sun Java 2	+
• Visual Basic .NET	+
• Delphi	+
Programming tutorials
• C	+	+	+
• C#	+
• Visual Basic .NET	+
• Delphi	+

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VeriLook SDK System Requirements

• PC with x86 (32bit) or x86-64 (64bit) compatible processors or Mac with x86 or PowerPC compatible processors. 2GHz or better processor is recommended.
• At least 128 MB of free RAM should be available for the application. Additional RAM is required for applications that perform 1-to-many identification, as all biometric templates need to be stored in RAM for matching. For example, 10,000 templates (each containing 1 face record) require about 24 MB of additional RAM.
• Free space on hard disk drive (HDD):
  • at least 1 GB required for the development.
  • 100 MB required for VeriLook components deployment.
  • Additional space would be required in these cases:
    • VeriLook does not require the original face image to be stored for the matching; only the templates need to be stored. However, storing face images on hard drive for the potential future usage is recommended.
    • Usually a database engine runs on a separate computer (back-end server). However, DB engine can be installed on the same computer for standalone applications. In this case HDD space for templates storage must be available. For example, 10,000 templates (each containing 1 face record) stored using a relational database would require about 30 MB of free HDD space. Also, the database engine itself requires HDD space for running. Please refer to HDD space requirements from the database engine providers.
• Camera or webcam. These cameras are supported by VeriLook:
  • Any webcam or camera that is accessible using:
    • DirectShow interface for Microsoft Windows platform.
    • Video4Linux interface for Linux platform.
    • QuickTime interface for Mac platform.
  • Also these specific models of high-resolution cameras are supported:
    • Axis M1114 camera (Microsoft Windows only)
    • Cisco 4500 IP camera (Microsoft Windows and Linux)
    • IrisGuard IG-AD100 – face & iris camera (Microsoft Windows only)
    • Mobotix DualNight M12 IP camera (Microsoft Windows and Linux)
    • PiXORD N606 camera (Microsoft Windows and Linux)
    • Prosilica GigE Vision camera (Microsoft Windows and Linux)
    • VistaFA2 / VistaFA2E face & iris cameras (Microsoft Windows only)
    • VistaMT Multimodal Biometric Device (Microsoft Windows only)
• Database engine or connection with it. VeriLook templates can be saved into any DB (including files) supporting binary data saving. VeriLook Extended SDK contains the following support modules for Matching Server:
  • Microsoft SQL Server (only for Microsoft Windows platform);
  • PostgreSQL (for Microsoft Windows and Linux platform);
  • MySQL (for Microsoft Windows and Linux platforms);
  • Oracle (for Microsoft Windows and Linux platforms);
  • SQLite (for all platforms).
• Network/LAN connection (TCP/IP) for client/server applications. Also, network connection is required for using Matching server component (included in VeriLook Extended SDK). Communication with Matching server is not encrypted therefore, if communication must be secured, a dedicated network (not accessible outside the system) or a secured network (such as VPN; VPN must be configured using operating system or third party tools) is recommended.
• Microsoft Windows specific requirements:
  • Microsoft Windows 2000/XP/2003/2008/Vista/7, 32-bit or 64-bit.
  • Microsoft .NET framework 2.0 or newer (for .NET components usage).
  • Microsoft DirectX 9.0 or later (for camera/webcam usage).
  • One of following development environments for application development:
    • Microsoft Visual Studio 2005 SP1 or newer (for application development under C/C++, C#, Visual Basic .Net)
    • Sun Java 1.5 SDK or later
    • Microsoft Visual Basic 6
    • Delphi 7
• Linux specific requirements:
  • Linux 2.6 or newer kernel, 32-bit or 64-bit.
  • glibc 2.3.6 or newer
  • Video4linux (for camera/webcam usage)
  • GTK+ 2.10.x or newer libs and dev packages (to run SDK samples and applications based on them)
  • GCC-4.0.x or newer (for application development)
  • GNU Make 3.81 or newer (for application development)
  • Sun Java 1.5 SDK or later (for application development with Java)
  • pkg-config-0.21 or newer (optional; only for Matching Server database support modules compilation)
• Mac OS X specific requirements:
  • Mac OS X (version 10.4 or newer)
  • QuickTime (for camera/webcam usage)
  • XCode 2.4 or newer (for application development)
    

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Technical Specifications

All specifications are given for Intel Core2 processor with 4 cores running at 2.66 GHz

640 x 480 pixels is the recommended minimal image size for VeriLook algorithm.

75 pixels is the recommended minimal distance between eyes for a face on image or video stream to perform face template extraction.

VeriLook has certain tolerance to face posture that assures face enrollment convenience:

• head roll (tilt) – ±180 degrees (configurable);
  ±15 degrees recommended as it is the fastest setting which is usually sufficient for most near-frontal face images.
• head pitch (nod) – ±15 degrees from frontal position.
• head yaw (bobble) – ±15 degrees from frontal position.

All face templates should be loaded into RAM before identification, thus the maximum face template database size is limited by the amount of available RAM.

VeriLook face template matching algorithm can use more than one processor core on multi-core processors allowing to increase template matching speed. The template matching speeds in the table below are given as a range, where the smaller number means matching speed using 1 processor core, while the larger number means matching speed using all 4 processor cores.

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Reliability and Performance Test Results

All tests were performed on Intel Core2 processor with 4 cores running at 2.66 GHz.

We present the testing results to show how VeriLook 5.0 technical specifications correspond the practical algorithm's performance and reliability evaluations. Face images from FRGC database were used for testing, thus the testing results can be compared with testing results of other algorithms.

Experiment 1 and Experiment 2 were performed according to FRGC protocol:

• Experiment 1 measures performance on the recognition from frontal facial images taken under controlled illumination. The biometric samples in the target and query sets consist of a single controlled still image in high resolution.
• Experiment 2 is designed to examine the effect of multiple still images on performance. The biometric samples in the target and query sets are composed of the 4 controlled images of each person from a subject.

See Overview of the Face Recognition Grand Challenge (PDF) for more details on FRGC experiments protocol.

Each experiment was performed 2 times to test different scenarios:

• Test 1 maximized matching accuracy. VeriLook 5.0 algorithm reliability in this test is shown on the ROC charts as blue curves for Experiment 1 and magenta curves for Experiment 2.
• Test 2 minimized template size. VeriLook 5.0 algorithm reliability in this test is shown on the ROC charts as red curves for Experiment 1 and orange curves for Experiment 2.

These sets of ROC curves were calculated using sertain subsets of FRGC database for each experiment and test according to FRGC protocol:

• ROC I – gallery and probe photos were taken within half of the year.
• ROC II – gallery and probe photos were taken within one year.
• ROC III – gallery and probe photos were taken with time lapse of at least half of the year but within 1.5 year.

Notes:

• Template matching was performed using all 4 cores of the processor.
• Part of images in the FRGC database is 1600 x 1200 pixels, and the other part is 2272 x 1704 pixels, as the images for this database were obtained with digital photo camera. The technical specifications above are given for 640 x 480 pixels images that are common for webcams.
• Head roll, pitch and yaw were set to ±15° during all experiments and tests.
• No score normalization techniques were applied while calculating these ROC curves, although FRGC protocol allowed to use score normalization.

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