Facool

538 views
466 views

Published on

Published in: News & Politics
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
538
On SlideShare
0
From Embeds
0
Number of Embeds
40
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Facool

  1. 1. What is F a c o o l ? A Brief Introduction Facool
  2. 3. Face & Name Association <ul><li>1. Initialize , t = 0; </li></ul><ul><li>2. Enumerate faces in database, calculate </li></ul><ul><li>3. , if , terminate procedure and is the final membership function. </li></ul><ul><li>Let t = t + 1, and go to step 2. </li></ul>
  3. 4. F & N Association Contrived Example Sim = 0.50 Rec =-0.14 Sim = 0.90 Rec = 0.60 Sim = 0.60 Rec =-0.09 Bill Clinton = 4/9 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 3/5 Dick = 2/5 Dick Morris = 2/5 Bill Clinton = 2/5 John Kerry = 1/5 Bill Clinton = 4/9 + (3/5 * 0.6 - 2/5 * 0.14)/2 = 0.624 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 3/5 + (4/9 * 0.6 - 2/5 * 0.09)/2 = 0.715 Dick = 2/5 - 2/5 * 0.09 = 0.364 Dick Morris = 2/5 - 2/5 * 0.09 = 0.364 Bill Clinton = 2/5 - (4/9 * 0.14 + 3/5 * 0.09)/2 = 0.342 John Kerry = 1/5 Threshold = 0.75
  4. 5. F & N Association Contrived Example Sim = 0.50 Rec =-0.14 Sim = 0.90 Rec = 0.60 Sim = 0.60 Rec =-0.09 Bill Clinton = 0.624 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 0.715 Dick = 0.364 Dick Morris = 0.364 Bill Clinton = 0.342 John Kerry = 1/5 Bill Clinton = 4/9 + (0.715 * 0.6 - 0.342 * 0.14)/2 = 0.6 35 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 3/5 + (0.624 * 0.6 - 0.342 * 0.09)/2 = 0.7 72 Dick = 2/5 - 0.364 * 0.09 = 0.36 7 Dick Morris = 2/5 - 0.364 * 0.09 = 0.36 7 Bill Clinton = 2/5 - (0.624 * 0.14 + 0.715 * 0.09)/2 = 0.3 24 John Kerry = 1/5 Threshold = 0.75
  5. 6. F & N Association Contrived Example Sim = 0.50 Rec =-0.14 Sim = 0.90 Rec = 0.60 Sim = 0.60 Rec =-0.09 Bill Clinton = 0.6 35 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 0.7 72 Dick = 0.36 7 Dick Morris = 0.36 7 Bill Clinton = 0.3 24 John Kerry = 1/5 Bill Clinton = 4/9 + (0.772 * 0.6 - 0.324 * 0.14)/2 = 0.6 5 3 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 3/5 + (0.635 * 0.6 - 0.324 * 0.09)/2 = 0.7 7 6 Dick = 2/5 - 0.367 * 0.09 = 0.36 7 Dick Morris = 2/5 - 0.367 * 0.09 = 0.36 7 Bill Clinton = 2/5 - (0.635 * 0.14 + 0.772 * 0.09)/2 = 0.3 2 1 John Kerry = 1/5 Threshold = 0.75
  6. 7. F & N Association Contrived Example Sim = 0.50 Rec =-0.14 Sim = 0.90 Rec = 0.60 Sim = 0.60 Rec =-0.09 Bill Clinton = 0.6 5 3 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 0.7 7 6 Dick = 0.36 7 Dick Morris = 0.36 7 Bill Clinton = 0.3 2 1 John Kerry = 1/5 Bill Clinton = 4/9 + (0.776 * 0.6 - 0.321 * 0.14)/2 = 0.6 5 4 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 3/5 + (0.653 * 0.6 - 0.321 * 0.09)/2 = 0.7 81 Dick = 2/5 - 0.367 * 0.09 = 0.36 7 Dick Morris = 2/5 - 0.367 * 0.09 = 0.36 7 Bill Clinton = 2/5 - (0.653 * 0.14 + 0.776 * 0.09)/2 = 0.3 19 John Kerry = 1/5 Threshold = 0.75
  7. 8. F & N Association Contrived Example Sim = 0.50 Rec =-0.14 Sim = 0.90 Rec = 0.60 Sim = 0.60 Rec =-0.09 Bill Clinton = 0.6 5 4 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 0.7 81 Dick = 0.36 7 Dick Morris = 0.36 7 Bill Clinton = 0.3 19 John Kerry = 1/5 Bill Clinton = 4/9 + (0.781 * 0.6 - 0.319 * 0.14)/2 = 0.6 5 7 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 3/5 + (0.654 * 0.6 - 0.319 * 0.09)/2 = 0.7 8 2 Dick = 2/5 - 0.367 * 0.09 = 0.36 7 Dick Morris = 2/5 - 0.367 * 0.09 = 0.36 7 Bill Clinton = 2/5 - (0.654 * 0.14 + 0.781 * 0.09)/2 = 0.3 19 John Kerry = 1/5 Threshold = 0.75
  8. 9. F & N Association Contrived Example Sim = 0.50 Rec =-0.14 Sim = 0.90 Rec = 0.60 Sim = 0.60 Rec =-0.09 Bill Clinton = 0.657 Peter Mcdermott = 1/9 Paul Farmer = 4/9 Bill Clinton = 0.783 Dick = 0.367 Dick Morris = 0.367 Bill Clinton = 0.319 John Kerry = 1/5 Threshold = 0.75 ……… ... Bill Clinton Bill Clinton Dick Morris
  9. 10. Index & Retrieval Approach <ul><li>1. Setup set table Idx [1~ D , 0~ L ]; </li></ul><ul><li>2. Idx [ i , f k ( i )] ∪{ k }-> Idx [ i , f k ( i )]. </li></ul>Note: f k is the k face image. Indexing & Storing: <ul><li>1. Setup array Vot [1~ n ]; </li></ul><ul><li>2. Vot [ Idx [ i , g ( i )]]+ w ( i )-> Vot [ Idx [ i , g ( i )]]. </li></ul>Note: g is the input face image, w is the weight at i . Retrieving:
  10. 11. Index Approach Contrived Example Gray Level Dimension 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Image 1: Image 2: 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
  11. 12. Retrieval Approach Contrived Example 1 Gray Level Dimension 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Retrieving Image: Vote 1: Vote 2: ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
  12. 13. Thank you! Try www.facool.net with computer or mobile device now!

×