TY - GEN
T1 - Optical flow estimation using Laplacian Mesh Energy
AU - Li, Wenbin
AU - Cosker, Darren
AU - Brown, Matthew
AU - Tang, Rui
PY - 2013/10/3
Y1 - 2013/10/3
N2 - In this paper we present a novel non-rigid optical flow algorithm for dense image correspondence and non-rigid registration. The algorithm uses a unique Laplacian Mesh Energy term to encourage local smoothness whilst simultaneously preserving non-rigid deformation. Laplacian deformation approaches have become popular in graphics research as they enable mesh deformations to preserve local surface shape. In this work we propose a novel Laplacian Mesh Energy formula to ensure such sensible local deformations between image pairs. We express this wholly within the optical flow optimization, and show its application in a novel coarse-to-fine pyramidal approach. Our algorithm achieves the state-of-the-art performance in all trials on the Garg et al. dataset, and top tier performance on the Middlebury evaluation.
AB - In this paper we present a novel non-rigid optical flow algorithm for dense image correspondence and non-rigid registration. The algorithm uses a unique Laplacian Mesh Energy term to encourage local smoothness whilst simultaneously preserving non-rigid deformation. Laplacian deformation approaches have become popular in graphics research as they enable mesh deformations to preserve local surface shape. In this work we propose a novel Laplacian Mesh Energy formula to ensure such sensible local deformations between image pairs. We express this wholly within the optical flow optimization, and show its application in a novel coarse-to-fine pyramidal approach. Our algorithm achieves the state-of-the-art performance in all trials on the Garg et al. dataset, and top tier performance on the Middlebury evaluation.
UR - http://dx.doi.org/10.1109/CVPR.2013.315
UR - http://www.cv-foundation.org/openaccess/CVPR2013.py
U2 - 10.1109/CVPR.2013.315
DO - 10.1109/CVPR.2013.315
M3 - Chapter in a published conference proceeding
T3 - IEEE Conference on Computer Vision and Pattern Recognition
SP - 2435
EP - 2442
BT - 2013 IEEE Conference on Computer Vision and Pattern Recognition
PB - IEEE
T2 - IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
Y2 - 25 June 2013 through 27 June 2013
ER -