It actually depends on the contrast in the image. The lower the contrast, the higher the motion can be. In low contrast images you have flat gradients. So what you do in lucas kanade is that you use the gradient to estimate the motion. More precicely you use first order expansion of the L2 based costfunction. Therefore first order expansion can only estimate good results close to the point you are looking at. So flat gradients mean that the distance can be higher cauze the error is lower.
@41:25 Today a function can be named a great mathematical discovery and understanding. But in 200 years no one will be educated enough to learn anything, muchless a great function!
55:10 the last line should be H not H inverse, should be a typo in the slides.
It actually depends on the contrast in the image. The lower the contrast, the higher the motion can be. In low contrast images you have flat gradients. So what you do in lucas kanade is that you use the gradient to estimate the motion. More precicely you use first order expansion of the L2 based costfunction. Therefore first order expansion can only estimate good results close to the point you are looking at. So flat gradients mean that the distance can be higher cauze the error is lower.
11:15 Any good resources on where to look to go further in MTMC ?!!
thnx a million time u saved my life with this video
Any tutorials on pyramid implementation ?
Hi, the presentasion link is unavailable. Can you provide the new one?
Hello, does anyone know what is the work at 12:09? the one about tracking with multiple fixed & non-overlapping cameras.
is that understandable for you?
What is the limitation for the large motion? ... he said if the frames has large motion we need to use pyramids .... how much this large?
thx a lot
Are you missing a ")" around W(x:p)
Thank you!
Is anybody here who has dr Mubarak speech in this presenation? pls!!!
Course Homepage: www.crcv.ucf.edu/courses/cap5415-fall-2012/
Sir where can we get the matlab implementation of this Algorithm
@41:25 Today a function can be named a great mathematical discovery and understanding. But in 200 years no one will be educated enough to learn anything, muchless a great function!