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• In ShowcaseDemo project on Windows, the appropriate function is worker_DoWorkVideo() .

• In FaceTracker2 sample project on Windows, the appropriate function is CVisionExampleDoc::trackFromVideo().

• In VisageTrackerDemo sample project on macOS, the appropriate function is trackingVideoThread().

Please search source code of each sample for the exact location.

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The maximum number of faces that can be tracked simultaneously is internally limited to 20 for performance reasons.

Using VisageFeaturesDetector API Reference → VisageFeaturesDetector, any number of faces can be detected in an image.

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The tracking distance depends on the camera resolution. For the face to be detected and tracked, it should be at least 30 pixels wide in the image. For example, for a webcam with resolution 1920×1080 (Logitech C920), the tracker can be configured to detect and track faces up to ~7.25 meters from the camera (with performance tradeofftrade-off).

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The online demo is based on visage|SDK for HTML5 and has some limitations due to the HTML5 implementation. For even better performance, you may want to download other visage|SDK for Windows, Android or iOS - each of these packages contains a native Showcase Demo ShowcaseDemo in which ear tracking can be tried.

If you are already developing using visage|SDK and want to enable ear tracking, you can use the ready-made configuration file “Facial Features Tracker - High - With Ears.cfg“. Ear tracking is enabled using the refine_ears configuration parameter.

Face Recognition

How far from a camera can a face be recognized?

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The technical demos in Android and Windows packages of visage|SDK include the source code intended to help you integrate liveness detection into your own application.

How do I perform identification of a person from a database?

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