I have the code, but its not documented yet... I could give it to you if you want to have a look, but I haven't thoroughly proofread it for bugs, and might not have time before december....
can you tell me what doesnt work ? i have received no complains so far... may be you did not read the reference document i sent... if possible post the error so that i can check
Hi, the basic smoothing operation that is done in the algorithm is to reduce the effects of noise in the data, so it cannot be avoided. If you really have noiseless data, and do not need much smoothing, you can change the appropriate parameters. You can refer to my documentation, but will eventually have to tweak the code to reduce the variance of the gaussian used for smoothing. If this is not too urgent (u can wait a week or so), I should be able to post additional documentation material, which you can use...
Hey,
Its a really nice piece of work, I am getting stuck at one part because, I want to reduce the number of points/resolution for which optical flow is computed,I believe that this will make the code faster.
Would be grateful,if anyone who has done this provides me with some help.
Hi all,I have a question.I compute the optical flow(u ,v) using LK and HS method. Now I want to compute the average angular error(AAE).But I don't know how.Do I need the ground truth optical flow (in .pcm file format)for compare the flow ?
Or any other way to compute the angular error?
thank u all.
I have made some minor modifications to your implementation of Brox's algorithm:
- Reflecting boundary conditions corresponds to mirror-extending the images. This can remove some of "unwanted" spurious flows at image boundaries.
- Added color channels (and different color spaces)
- 500 SOR Iterations is too much! If I remember correctly, Brox mentions much less SOR iterations. You can safely decrease it to around 50(or even less).
Let me know if you want me to send the modified code to you(Visesh).
Regarding the higher errors on the results:
- If I'm not mistaken, this implementation does not assume spatio-temporal smoothness(it's not 3D) and does not work on more than 2 images . In order to get nicer results you have to extend it to the 3D case.
I recently realized that Brox has already put his binaries(both for the ECCV04 and CVPR09 papers) online!
Thank you for this implementation. It is valuable in an educational way. But given that the bugs mentioned above are still in this package this gets only 3 stars from me. Also, you might be interested in this implementation which is a lot faster and produces very similar results:
http://people.csail.mit.edu/celiu/OpticalFlow/
