scale invariant "shapes_residual"

[beginlu]

Thanks for your great work, help me through the paper. But there is still one problem confuse me.
In matlab code, i found you transform the intermediate's "shapes_residual" to the "meanshape_resize" coordinate system, while the latter's bounding box is exactly the same as intermediate's shape. Which means the "shapes_residual" would depends on the image resolution, e.g. same image, if i double its size, the "shapes_residual" would be doubled, and the binary feature still the same. Would this affect the global regression? Why not just transform to the unique param's "meanshape"?

[jwyang]

Hi,

before global regression, shape_residual will be divided by the size of
bounding box of intermediate shape. Meanwhile, in the prediction stage, the
derived shape residual will times the size of bounding box of intermediate
shape. Therefore, if the image is scaled, the corresponding residuals will
not change as the binary feature. Hope this helps you.

Best,

On Wed, Dec 24, 2014 at 2:30 AM, beginlu notifications@github.com wrote:

Thanks for your great work, help me through the paper. But there is still
one problem confuse me.
In matlab code, i found you transform the intermediate's "shapes_residual"
to the "meanshape_resize" coordinate system, while the latter's bounding
box is exactly the same as intermediate's shape. Which means the
"shapes_residual" would depends on the image resolution, e.g. same image,
if i double its size, the "shapes_residual" would be doubled, and the
binary feature still the same. Would this affect the global regression? Why
not just transform to the unique param's "meanshape"?

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Jianwei Yang
Beijing University of Posts and Telecommunications
Institute of Automation, Chinese Academy of Sciences
14th floor in Intelligence Building
95 Zhongguancun East Road
Haidian District, Beijing 100190, China

杨健伟
北京邮电大学
中国科学院自动化研究所
北京海淀区中关村东路95号智能化大厦14层
邮政编码：100190

[beginlu]

Sorry for my carelessness, it's so obvious, and i just missed the 'normalizing' part.
I'm trying to implement it in c++ base on your code, it would make me a deeper understanding. Thx again.