I am starting a project soon where I need to create a method to automatically create landmarks on a set of images of human hands. I do not have a sample image but the images are taken with the same background and stable lightning conditions. The images probably look similar to this one, (but should be the other side of the hand).
My colleagues have defined some landmarks, but I would like to first just detect the tips of the fingers and the inner most part between the fingers. I was looking into potential solutions and active shape or active appearance models look like a good idea, although they might also be an overkill. I was also thinking about just creating a template of a hand with landmarks, segmenting the hand with foreground/background segmentation (probably thresholding, PCA or even MRFs if the others fail a lot), and then do an affine + non-rigid registration to transfer the landmarks.
What I am asking is:
- Are the methods that I mention for solving this task appropriate?
- Is there any solution out there that already solves this problem?
- Referrals to code to do some of this is appreciated.
- Do you have other better suited ideas to solve this problem?
I am going to play around with the images in this dataset, which already have lots of annotated landmarks.
Yes, this is my first post, so if you have ideas for other tags to include let me know. Also if you need further clarifications, don't hesitate to ask!