How are Faces Encoded for Image Recognition?

Click For Summary
Eigenvectors play a crucial role in face recognition by enabling the representation of facial images as mathematical constructs. In this context, pixels from an image are transformed into a collection of numbers, often organized in vectors or matrices. This transformation is essential for analyzing and recognizing faces. The concept of "eigenfaces" is particularly relevant, as it utilizes eigenvectors derived from the covariance matrix of the pixel data to identify and differentiate facial features. Understanding this mathematical framework is key to grasping how face recognition systems operate. For a deeper exploration of the topic, resources such as the article on eigenfaces can provide valuable insights.
WWGD
Science Advisor
Homework Helper
Messages
7,772
Reaction score
13,006
Hi all,
I think I have an idea of how the Mathematical aspects of Face recognition work. But I am curious as to what an eigenvector would be in this respect. I am trying to understand it through finding out how pixels are encoded: What map takes a pixel into a collection of numbers/vector/matrix?
Thanks.
 
Computer science news on Phys.org
Thread 'ChatGPT Examples, Good and Bad'
I've been experimenting with ChatGPT. Some results are good, some very very bad. I think examples can help expose the properties of this AI. Maybe you can post some of your favorite examples and tell us what they reveal about the properties of this AI. (I had problems with copy/paste of text and formatting, so I'm posting my examples as screen shots. That is a promising start. :smile: But then I provided values V=1, R1=1, R2=2, R3=3 and asked for the value of I. At first, it said...

Similar threads

  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 11 ·
Replies
11
Views
4K
  • · Replies 7 ·
Replies
7
Views
1K
Replies
31
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 6 ·
Replies
6
Views
6K