Add facial recognition and biometric identification to your applications. FaceSDK is a multi-platform library enabling Microsoft Visual C++, C#, Objective C, Swift, Java, VB, Delphi, Python developers implement fast and precise face recognition and identification in their applications. Working in 32-bit and 64-bit systems, FaceSDK is used to build Web, Windows, Linux, Mac OS, iOS and Android applications, and enables face-based biometric authentication on still images and real-time video streams.
FaceSDK offers fast and precise face recognition and identification. Its consistent recognition rates in any lighting conditions and its ability to be used in conjunction with any webcam make FaceSDK a leader in biometric authentication systems. The SDK works with large and small still images, and offers true real-time support by recognizing and identifying faces in video streams. The innovative video recognition algorithms implement true motion-based video identification, automatically recognizing and tagging all faces encountered in a video stream with no prior enrolment required.
FaceSDK utilizes today's multiple-core, multi-CPU computing to the limit. This and other performance optimizations lead to dramatically increased performance, allowing surefooted identification and recognition of 70 facial features in real time.
SDK is loaded with features and comes with a host of samples in a variety of programming languages, allowing Web and desktop developers implement advanced face recognition and identification tasks in a matter of minutes. SDK has been used by the entertainment industry and security specialists, software vendors, and developers of graphic suites to automate a variety of face identification and facial feature recognition tasks, including hands-free authentication and logon systems. Real-time biometric authentication systems can quickly and easily be built around FaceSDK. A variety of photo processing use FaceSDK as their face recognition engine.
v4.0 [Dec 8, 2011]
FaceSDK 4.0 improves the speed and accuracy of facial feature detection, with 66 facial features detected in real-time. The 4.0 version supports multi-core processors to boost the performance of face recognition, face detection, and facial feature detection. Support for MJPEG IP cameras has been added.
The increase in speed when using all cores of an Intel i7 processor is 315% for facial feature detection,* 250% for face detection, 130% for face template creation, and 225% for eye detection. The facial feature detection speed is 9.3 frames per second (including face detection using real-time parameters).
Support for Java language has been added. A CImage class for easy manipulation with images on .NET has been added. JPEG file loading was speeded up by 390%.**
More samples were added:
* Lookalikes samples (C#-DB, C#-SQLite, C-DB, C-SQLite) to work with Microsoft SQL and SQLite databases (C#.NET, C )
* LiveFacialFeatures to detect facial features in real-time (C#.NET, VB.NET, Java, Delphi, C )
* IPCamera to work with IP cameras (C#.NET, VB.NET, Java, C )
* FaceTracking, FacialFeatures, and LiveRecognition now feature a Java version.
The LiveRecognition demo application (available on the Welcome screen after the installation) introduces new, more robust usage of FaceSDK recognition algorithms. The Facial Feature Demo application, which tracks a person's facial features in real-time, was added.
Functions to control the number of cores used by FaceSDK were added.
Unicode filename support on Windows was added.
