I was digging into OpenCV's implementation of SIFT descriptor extraction. I came upon some puzzling code to get the radius of the interest point neighborhood. Below is the annotated code, with variable names changed to be more descriptive:
// keep octave below 256 (255 is 1111 1111) int octave = kpt.octave & 255; // if octave is >= 128, ...???? octave = octave = 0 ? 1.0f/(1
I understand that this has something to do with converting to the scale from which the interest point was taken (I have read Lowe's paper), but I can't connect the dots to the code. Specifically, I don't understand the first 3 lines and last line.
I need to understand this to create a similar local point descriptor for motion.
I don't understand the first 3 lines
Indeed this SIFT implementation encodes several values within the KeyPoint octave attribute. If you refer to the line 439 you can see that:
kpt.octave = octv + (layer
Which means the octave is stored within the first byte block, the layer within the second byte block, etc.
So kpt.octave & 255 (which can be found within the unpackOctave method) just masks out the keypoint octave to retrieve the effective octave value.
Also: this SIFT implementation uses a negative first octave (int firstOctave = -1) to work with an higher resolution image. Since the octave indices start at 0, a mapping is computed:
octave index = 0 => 255 octave index = 1 => 0 octave index = 2 => 1 ...
This mapping is computed at line 790:
kpt.octave = (kpt.octave & ~255) | ((kpt.octave + firstOctave) & 255);
Thus the second line above is just a way to map back these values:
octave = 255 => -1 octave = 0 => 0 octave = 1 => 1 ..
And the third line is just a way to compute the scale, taking into account that negative octaves give a scale > 1, e.g 1 gives 2 for octave = -1 which means it doubles the size.
[I don't understand] last line.
Basically it corresponds to the radius of a circle that wraps a squared patch of dimension D, hence the sqrt(2) and the division by 2. D is computed by multiplying:
- the keypoint scale,
- a magnification factor = 3,
- the width of descriptor histogram = 4, rounded up to the next integer (hence the +1)
Indeed you can find a detailed description within vlfeat's SIFT implementation:
The support of each spatial bin has an extension of SBP = 3sigma pixels, where sigma is the scale of the keypoint. Thus all the bins together have a support SBP x NBP pixels wide. Since weighting and interpolation of pixel is used, the support extends by another half bin. Therefore, the support is a square window of SBP x (NBP + 1) pixels. Finally, since the patch can be arbitrarily rotated, we need to consider a window 2W += sqrt(2) x SBP x (NBP + 1) pixels wide.
At last I greatly recommend you to refer to this vlfeat SIFT documentation.
