In matlab, there is a built-in function to calculate properties of a region.
http://www.mathworks.com/help/images/ref/regionprops.html#bqkf8jf
And as said in help message:
'Eccentricity' — Scalar that specifies the eccentricity of the ellipse that has the same second-moments as the region. The eccentricity is the ratio of the distance between the foci of the ellipse and its major axis length. The value is between 0 and 1. (0 and 1 are degenerate cases; an ellipse whose eccentricity is 0 is actually a circle, while an ellipse whose eccentricity is 1 is a line segment.) This property is supported only for 2-D input label matrices.
So, the idea is to fit using a ellipse with same second-moments as the region.
What does it mean?
The answer is in this thread:
http://stackoverflow.com/questions/1532168/what-are-the-second-moments-of-a-region
To simplify, the idea is to calculate the co-variance matrix, then do eign-value decomposition. Eigen-values are those axis length, minor and major one. While eigen-vectors are the directions of minor/major axis.
length of major axis = 2a, minor axis = 2b, then the foci = c, then:
eccentricity E = c/a = sqrt(1-(b/a)^2)
a^2-b^2 = c^2.
Showing posts with label computer vision. Show all posts
Showing posts with label computer vision. Show all posts
Monday, June 30, 2014
Monday, April 28, 2014
Face recognition again
These days, some interesting news in face recognition field are re-posted widely on social network.
DeepFace: Closing the Gap to Human-Level Performance in Face Verification (Facebook AI lab)
It is said the performance is close to human being.
Then, more incredible, someone claimed their algorithm outperforms humankind.
http://www.zhizhihu.com/html/y2014/4520.html
https://medium.com/the-physics-arxiv-blog/2c567adbf7fc
http://www.52ml.net/14704.html
face++
http://www.faceplusplus.com/uc/app/home?app_id=14807
Most of the result is achieved on LFW (labeled face in the wild)
http://vis-www.cs.umass.edu/lfw/index.html
My adviser want me to do some face recognition stuff.
DeepFace: Closing the Gap to Human-Level Performance in Face Verification (Facebook AI lab)
It is said the performance is close to human being.
Then, more incredible, someone claimed their algorithm outperforms humankind.
http://www.zhizhihu.com/html/y2014/4520.html
https://medium.com/the-physics-arxiv-blog/2c567adbf7fc
http://www.52ml.net/14704.html
face++
http://www.faceplusplus.com/uc/app/home?app_id=14807
Most of the result is achieved on LFW (labeled face in the wild)
http://vis-www.cs.umass.edu/lfw/index.html
My adviser want me to do some face recognition stuff.
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