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I-TAG: AUTO FACE TAGGING ASSISTANT by Duygu Sarıkaya,Ahsen Yergök,Dilek Demirbaş

I-TAG: AUTO FACE TAGGING ASSISTANT by Duygu Sarıkaya,Ahsen Yergök,Dilek Demirbaş. OUTLINE. Motivation Problem Definition Existing Systems Proposed Solution How it Works Face Detection Eigenface User Interface Demo Conclusion. PROBLEM DEFINITON. Tagging Manuel Time consuming

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I-TAG: AUTO FACE TAGGING ASSISTANT by Duygu Sarıkaya,Ahsen Yergök,Dilek Demirbaş

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  1. I-TAG: AUTO FACE TAGGINGASSISTANT by Duygu Sarıkaya,Ahsen Yergök,Dilek Demirbaş

  2. OUTLINE • Motivation • Problem Definition • Existing Systems • Proposed Solution • How it Works • Face Detection • Eigenface • User Interface • Demo • Conclusion

  3. PROBLEM DEFINITON • Tagging • Manuel • Time consuming • tedious

  4. EXISTING SYSTEMS

  5. EXISTING SYSTEMS • Detect faces

  6. EXISTING SYSTEMS

  7. EXISTING SYSTEMS • Tag photos of self

  8. EXISTING SYSTEMS • IPhoto • Faces and Places

  9. PROPOSED SOLUTION • Automatically Tag Faces • based on facial properties

  10. FACE DETECTION • Detect Faces in a Given Image

  11. EIGENFACE • Data Set

  12. EIGENFACE • Step 1 • Transformation • Step 2 • Mean Image

  13. EIGENFACE • Step 3 • Difference ”Φ” • Step 4 • Calculateeigenvectors and eigenvalues

  14. EIGENFACE • Step 5

  15. EIGENFACE • Recognition • A new face • Best description for the input image • Euclidian Distance • Two threshold value • Unknown face • Another image

  16. Expected results • automated-tagging system • İnstead of a time-consuming system “i-Tag” • But the success rates are highly dependant on; • illumination • Size • color changes of the photographs

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