5 ms·
The original post really highlights the "problem with computer vision" - finding the coke can is fairly easy (SIFT), although the author goes off on some other
by strebler 14y ago
The original post really highlights the "problem with computer vision" - finding the coke can is fairly easy (SIFT), although the author goes off on some other random approach that I doubt would work very well. The field certainly has its share of Do-It-Yourselfers, plus it's also quite common to outsource labour overseas.
As for fees, it's entirely reflective of a) how much money the problem is costing the client and b) your ability to prove to them your value to the client. Clients do not always respect the complexity of the problems they're facing, so it's easier to work with those who have tried for themselves.
For what it's worth, we're hiring right now in this space (computer vision software development), located in Ottawa, Canada: http://ca.indeed.com/job/software-engineer-71a851096a104223 http://ca.indeed.com/job/software-engineer-71a851096a104223
- buq2 14y agoI don't see any problem with the original solution. It is classic (but little bit old fashioned) way of detecting objects, far from random. I also think that you oversimplify the SIFT solution. You use sift, then what? Match the feature vectors, get bunch of possible correspondence points, prune outliers using 3D model of a cylinder (or assume that the face of the can is flat plane and just use homography) and robust fitting, validate fitting, find other cans, if none found change parameters? No preprocessing? Ignore color? Etc. Not so straight forward. SIFT is faster than generalized HoughTF in this case, use of points instead of whole objects/blobs gives you nice ways to validate using 3D model, etc., but I would still not look down on some one who finds and implements this solutions as a student.
- strebler 14y agoYou're right, it's ok for a project. I guess what I meant was it's quite easy compared to the problems my company deals with every day. 30 images in 24 hours (I think it said) is kind of a problem. Given the constraints of the asker (all available in OpenCV), the solution I would suggest first is SIFT + homography, both easy to use and in OpenCV (sample code is around). Yes, there's a lot of other possibilities, but this would be an improvement over the original.
- tocomment 14y agoHey that sounds like a cool job but why does the candidate need to know java and c++?
- strebler 14y agoWell we do use both (and various others), but really what languages someone knows isn't such a big factor.