TY - GEN
T1 - Optical flow estimation using sparse gradient representation
AU - Nawaz, Muhammad Wasim
AU - Bouzerdoum, Abdesselam
AU - Phung, Son Lam
PY - 2011
Y1 - 2011
N2 - This paper introduces a sparsity based optical flow estimation method in digital video sequences. The method stems from the key observation that the gradient field of optical flow, in digital video sequences, is usually structured and sparse in spatial domain, provided there is a small number of multiple motions in the scene. The gradient field of motion vectors is formed by the pixels forming the edges of moving objects. We utilize this fact and formulate the optical flow estimation problem in sparse representation framework. We then use a minimization algorithm over ℓ 1 norm of the gradient flow field to find the solution to this problem. The proposed algorithm has been evaluated on Middlebury's benchmark video sequence database.
AB - This paper introduces a sparsity based optical flow estimation method in digital video sequences. The method stems from the key observation that the gradient field of optical flow, in digital video sequences, is usually structured and sparse in spatial domain, provided there is a small number of multiple motions in the scene. The gradient field of motion vectors is formed by the pixels forming the edges of moving objects. We utilize this fact and formulate the optical flow estimation problem in sparse representation framework. We then use a minimization algorithm over ℓ 1 norm of the gradient flow field to find the solution to this problem. The proposed algorithm has been evaluated on Middlebury's benchmark video sequence database.
KW - Optical flow
KW - computer vision
KW - sparse representation
KW - variational flow model
UR - http://www.scopus.com/inward/record.url?scp=84856249696&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2011.6116220
DO - 10.1109/ICIP.2011.6116220
M3 - Conference contribution
AN - SCOPUS:84856249696
SN - 9781457713033
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2681
EP - 2684
BT - ICIP 2011
T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011
Y2 - 11 September 2011 through 14 September 2011
ER -