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Dynamic Face Detection Module for Skin Color & Background Modeling

Leveraging advanced algorithms, this module combines skin color modeling and dynamic background modeling to accurately detect faces. It utilizes Random Field Models and Evidence Aggregation for improved decision confidence. The output includes skin masks for precise detection while reducing false positives.

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Dynamic Face Detection Module for Skin Color & Background Modeling

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  1. Face Detector Output & Original Image Module 1 Skin Color Model Dynamic Background Modeler Module 2 RF 1 RF 2 RF 3 RF 4 RF 5 Evidence Aggregator Face Non Face Decision Confidence * RF: Random Field Model

  2. Face Detection Output Extra-region of extraction for background model

  3. Face Detection Output Face Detection Output Skin Mask Skin Mask False Detection True Detection C-4 C-3 C-1 C0 C1 C2 C0 C-2 C4 C3 Sample for Random Field learning R1 R2 R3 R4 R5 R6 R7 R8 R9 R10

  4. N3 N3 N1 N1 C-4 C-3 C-2 C0+ C4 C-1 C0- C2 C3 C1 N2 N2 N4 N4 N5 Pose 3 Pose 2 Pose 1

  5. Confidence 1 0.8 0.6 0.4 0.2 0 Log Likelihood LL LU

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