• Save
Face recognition
Upcoming SlideShare
Loading in...5
×
 

Face recognition

on

  • 1,096 views

ppt by sandeep sharma

ppt by sandeep sharma

Statistics

Views

Total Views
1,096
Views on SlideShare
1,096
Embed Views
0

Actions

Likes
3
Downloads
0
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Face recognition Face recognition Presentation Transcript

  • Presentation by: Sandeep Sharma CSE
  •  Introduction Types of face recognition How it works Working steps Algorithms used Problems faced Future uses Conclusion
  •  Inthe 1960s, scientists began work on using the computer to recognize human faces. Since then, face recognition technology has come a long way.A Face recognition software is based on the ability to recognize a face by measuring the various features of the face.
  •  Every face has numerous distinguishable landmarks,the different peaks and valleys that make facial features. Face recognition system defines these landmarks as nodal points.Each human face has approximately 80 landmarks. Some of them are: • Distance between the eyes • Width of the nose • Shape of the cheek bones • Length of the jaw line
  •  2D Face Recognition 3D Face Recognition
  •  In past,face recognition system relied on comparing 2D images with another 2D images in data base. Person should be looking towards the camera. Even the slight variance in light or smile of a person creates the problem. This makes the system less effective.
  •  Capturing the real time images of the person. Uses distinctive features of face. Can be used in darkness. Has the ability to recognize the person through different angles.
  •  2D Face Recognition 3D Face Recognition
  •  Detection:Acquiring an image by scanning or by using a video image. Aligment:Once the face is detected the system identifies the head’s position,size and pose.
  •  Measurement: The system then measures the curves of the face on a sub-millimeter scale and creates a template. Representation: The system translates the template into a unique code.
  •  Matching:The 3D image is matched with 3D image in the Database. Verification:In verification the image is verified with the one image in the database and result is displayed side wise.
  •  Face recognition algorithms identify facial features by landmarks. Some of them are: • Principle Component Analysis(Eigenfaces) • Linear Discriminate Analysis. • Elastic Bunch Graph Matching. • Multilinear Subspace Learning(Tensor)
  •  The Person in disguise cannot be caught. Less effective in huge crowd.
  •  Technology is used by Law Enforcement Agencies. Can be used in Banking for identification. Can be used on airport for security purpose.
  •  At present it is most promising for small or medium scale applications.such as office access and computer log in. It still face great technical challenges for large scale deployments.such as airport security. Advancement in hardware and software needed. Can emerge as Backbone of security system.