TY - GEN
T1 - Large displacement optical flow computation without warping
AU - Steinbrücker, Frank
AU - Pock, Thomas
AU - Cremers, Daniel
PY - 2009
Y1 - 2009
N2 - We propose an algorithm for large displacement optical flow estimation which does not require the commonly used coarse-to-fine warping strategy. It is based on a quadratic relaxation of the optical flow functional which decouples data term and regularizer in such a way that the non-linearized variational problem can be solved by an alternation of two globally optimal steps, one imposing optimal data consistency, the other imposing discontinuity-preserving regularity of the flow field. Experimental results confirm that the proposed algorithmic implementation out-performs the traditional warping strategy, in particular for the case of large displacements of small scale structures.
AB - We propose an algorithm for large displacement optical flow estimation which does not require the commonly used coarse-to-fine warping strategy. It is based on a quadratic relaxation of the optical flow functional which decouples data term and regularizer in such a way that the non-linearized variational problem can be solved by an alternation of two globally optimal steps, one imposing optimal data consistency, the other imposing discontinuity-preserving regularity of the flow field. Experimental results confirm that the proposed algorithmic implementation out-performs the traditional warping strategy, in particular for the case of large displacements of small scale structures.
UR - http://www.scopus.com/inward/record.url?scp=77953178803&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2009.5459364
DO - 10.1109/ICCV.2009.5459364
M3 - Conference contribution
AN - SCOPUS:77953178803
SN - 9781424444205
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 1609
EP - 1614
BT - 2009 IEEE 12th International Conference on Computer Vision, ICCV 2009
T2 - 12th International Conference on Computer Vision, ICCV 2009
Y2 - 29 September 2009 through 2 October 2009
ER -