So, I am trying to implement the Scale Invariance Feature detector paper by Prof. David Lowe. I studied the paper but many of the concepts are unclear to me. Since I am new to Computer Vision(am a CS grad student having taken CV this spring), can you guys suggest some resources that might be helpful for understanding the paper thus aiding me in the implementation? Thanks a lot.
The base paper published by David Lowe is clearly explained by Dr. Mubarak sha in the following video.
https://www.youtube.com/watch?v=NPcMS49V5hg
This is one of the best explanation available.
If you cannot understand the paper but still need to get the concepts understand easily, I would suggest reading the following blog article and its associated articles. The writer has explained the concepts in really simple and attractive manner with very good visual aids.
http://aishack.in/tutorials/sift-scale-invariant-feature-transform-introduction/
Subhankar,
Ravimal provided an excellent source for a detailed explanation of the method. It is, however, an advanced topic in classic CV and not beginner's stuff. If you still have difficulties to understand it, try gathering basic concepts in CV before you endeavour the step of trying to understand SIFT. There are lots of introductory books and blogs about the basics. I suggest Haralick and Shapiro's CV book (it's 30 years old, but excellent with the basics - ypur library sghould have both volumes). Browse it in order to get an overview of the many concepts handled in SIFT. After that, try the lecture and the video provided by Manikandan again.
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