Interpreting OpenCV FaceRecognition predicted confidence values

asked 2012-08-20 11:08:49 -0500

lvicks gravatar image

updated 2012-08-20 11:10:06 -0500

I am toying with the various FaceRecognition algorithms, and I'd like to better understand the confidence values so that I can have a sense of when to ignore a match or when I can rely on a match.

Using the ATT face database, I did test 1 where I trained on the 40 faces then ran prediction on a known face (With unknown image of course). I then did a second test where I trained on 39 faces and ran prediction on an unknown face (happens to be the same image as used in test 1).

The values I got were:
Eigenspace
- 1806 when face known
- 2618 when face unknown

Fisherface
- 372 known
- 841 unknown

LBPH
- 36 known
- 55 unknown

If I am interpreting the algorithms correctly, Eigenspace and Fisherface work in a high dimension space and try to find the closest neighbor for a given test image. This means the confidence value will change depending on data set, and I can not have a simple threshold. Is there any other information I can gather, such as average distance between clusters, so that I can understand if I should keep or ignore a prediction?

In regards to LBPH, is this confidence acting the same way?

Many thanks

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Comments

It'll take some time to write the tutorial and source code, so please check back later. This could be some days, because I can only write it in my spare time.

Philipp Wagner gravatar imagePhilipp Wagner ( 2012-08-20 11:50:17 -0500 )edit