Luxand FaceSDK 1.0

Detect human faces and recognize facial features in your applications with Luxand FaceSDK.

Digital camera manufacturers spend millions of dollars developing face recognition technologies for their digital cameras. Digital Signal Processors (DSP) combined with face detection algorithms do the job in digital cameras, allowing for better autofocus and proper exposure. These DSPs can only recognize human faces, but don't go any further than that. Modern solutions do not provide facial feature detection, and hence their applications are limited.

Facial feature recognition allows automating common post-processing tasks such as red-eye removal and skin tone adjustment. Users of digital cameras benefit from more precise automatic adjustments and touch-ups that don't require user intervention. Enable face recognition in your software without the need to spend millions of dollars and with no DSP with Luxand FaceSDK!

Luxand FaceSDK employs sophisticated algorithms to detect frontal human faces on digital pictures quickly and reliably. The SDK processes the image, detects human faces, and returns the coordinates of 40 facial feature points including the eyes, eye corners, eyebrows, mouth corners, nose tip, and so on.

Developing morphing, animation or 3D software? Create a perfect 'skin' or a 3D head model automatically! Luxand FaceSDK can select human faces and return pictures that contain the coordinates of facial features, making it easy to match facial features of the photograph with the corresponding features on the 3D head.

Luxand FaceSDK is implemented as a highly compatible Win32 DLL, and supports popular development environments. Microsoft Visual C++ and Borland Delphi users get all necessary header files, making it easy to integrate with new or existing projects.

Create graphical editors or automatic red-eye removal products. Develop solutions for making 3D head models with a single photograph. Morph, animate or transform human faces with Luxand FaceSDK!

See also: face, face recognition, facial recognition, facial features, face detection, facial feature detection, facial feature recognition