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What is the theory for SmallBlurryImage::IteratePosRelToTarget() method ? #16
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This is described by section 6 of the ECCV 2008 paper "Improving the agility of keyframe-based SLAM". In short, we run ESM (similar to Lucas-Kanade) to align two images to each other over SE(2). |
@GeorgKlein
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1. WfromC maps a image-center-based coordinate frame to an
image-corner-based coordinate frame, as required by the warp function.
2. This looks like the partial differential of image intensity w.r.t.
rotation about the image center, computed by multiplying the differential
of image motion w.r.t. rotation by the differential of image intensity
w.r.t. image motion.
3. The optimization runs over three parameters: (0&1): translation (2):
rotation (3): intensity shift between images.
…On Tue, Feb 6, 2018 at 12:55 AM, Gordon Scott ***@***.***> wrote:
@GeorgKlein <https://github.com/georgklein>
I can not understand the code segment below in SmallBlurryImage::
IteratePosRelToTarget() method.
1.
SE2<> se2XForm = se2WfromC * se2CtoC * se2WfromC.inverse();
what does *se2WfromC* and *se2CtoC* mean and why make *se2XForm* in
that form ?
2.
v4Jac[2] = -(ir.y - irCenter.y) * v2SumGrad[0] + (ir.x - irCenter.x) *
v2SumGrad[1];
what does *v4Jac[2]* mean and why compute it like this ?
3.
dMeanOffset -= v4Update[3];
why use *v4Update[3]* to make *dMeanOffset* and compute the
*dFinalScore* ?
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I'm learning the PTAM code, but I cannot find the theory respond to the SmallBlurryImage::IteratePosRelToTarget() method linking https://github.com/Oxford-PTAM/PTAM-GPL/blob/master/Src/SmallBlurryImage.cc#L98-L205
I would appreciate it if you can tell me the theory or its thesis name.
I am looking forward to your reply, thank you.
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