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Mohit Gupta
Mohit Gupta

LDA Face Recognition Technique theory content excluding Math formulae

Engineering
1 of 10
Linear Discriminant Analysis (Face Recognition Technique)
INDEX  Introduction to Face Recognition Technique  Applications  Demonstration of Project Work  Conclusion
Introduction to Face Recognition Technique  Research Background Face recognition Is a technology for Identifying people based on Effective ID Information extracted by computers from facial pictures. With the development of Technology , development of digitalized Information requires secure authentication more than ever. Compare with biometric authentication method like finger prints, iris, palm print, face recognition system is more friendly and convenient and easier for Users to accept. This makes Face recognition technology a research Hotspot.
Difficulty in Face recognition  Speciality of Human Face -> Rotation -> Facial Expression  Influence from Environment -> Distance -> Size -> Illumination  Limitation On Computers -> Process data in a short time
Applications :  Bankruptcy prediction  Face recognition  Marketing  Biomedical studies  Data Mining
Steps involved in matching the faces from Database & LDA technique:
Result: - Out of 40 images 37 were recognized correctly.
How Artificial Intelligence used in storing & comparing human faces :
Conclusion:  In this System, Algorithm reached to a certain level of recognition rate  A better recognition rate can be achieved by getting more training images to form EigenSpace.
ThankU

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LDA presentation

  • 2. INDEX  Introduction to Face Recognition Technique  Applications  Demonstration of Project Work  Conclusion
  • 3. Introduction to Face Recognition Technique  Research Background Face recognition Is a technology for Identifying people based on Effective ID Information extracted by computers from facial pictures. With the development of Technology , development of digitalized Information requires secure authentication more than ever. Compare with biometric authentication method like finger prints, iris, palm print, face recognition system is more friendly and convenient and easier for Users to accept. This makes Face recognition technology a research Hotspot.
  • 4. Difficulty in Face recognition  Speciality of Human Face -> Rotation -> Facial Expression  Influence from Environment -> Distance -> Size -> Illumination  Limitation On Computers -> Process data in a short time
  • 5. Applications :  Bankruptcy prediction  Face recognition  Marketing  Biomedical studies  Data Mining
  • 6. Steps involved in matching the faces from Database & LDA technique:
  • 7. Result: - Out of 40 images 37 were recognized correctly.
  • 8. How Artificial Intelligence used in storing & comparing human faces :
  • 9. Conclusion:  In this System, Algorithm reached to a certain level of recognition rate  A better recognition rate can be achieved by getting more training images to form EigenSpace.