Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
A survey of image registration techniques
ACM Computing Surveys (CSUR)
Sizing and least-change secant methods
SIAM Journal on Numerical Analysis
A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
Trust-region methods
Alignment by maximization of mutual information
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Real-Time Tracking Using Trust-Region Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Appearance Models Revisited
International Journal of Computer Vision
Generalizing inverse compositional image alignment
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Applied Optimization with MATLAB Programming
Applied Optimization with MATLAB Programming
Automatic Panoramic Image Stitching using Invariant Features
International Journal of Computer Vision
Mutual Information for Lucas-Kanade Tracking (MILK): An Inverse Compositional Formulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Maximum a posteriori local histogram estimation for image registration
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
A novel algorithm for fitting 3-d active appearance models: applications to cardiac MRI segmentation
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Optimization of mutual information for multiresolution image registration
IEEE Transactions on Image Processing
Fast motion estimation using bidirectional gradient methods
IEEE Transactions on Image Processing
Bidirectional composition on Lie groups for gradient-based image alignment
IEEE Transactions on Image Processing
Automatic estimation of asymmetry for gradient-based alignment of noisy images on Lie group
Pattern Recognition Letters
Improving NCC-based direct visual tracking
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
| Hi-index | 0.00 |
Inverse compositional (IC) image alignment (Baker and Matthews in Int. J. Comput. Vis. 56(3):221---255, 2004) uses the symmetry between the roles of the fixed and moving images for faster processing. However, it requires implementation of compositional optimizer update steps. The IC approach can be viewed as an efficient way of computing the similarity measure derivative relative to the fixed image warp parameters. Since the mapping between the fixed and moving warp parameters is continuous and differentiable, this derivative can be converted into the moving warp space using the chain rule. This avoids the need for compositional update steps. Our generalization also allows the efficient second order method (ESM) (Malis in Proceedings of the 2004 IEEE International Conference on Robotics and Automation (ICRA04), pp. 1843---1848, 2004; Benhimane and Malis in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004; Malis and Benhimane in Robot. Auton. Syst. 52(1):39---52, 2005) to be applied to general parameterizations of the transformation.Experiments using multiple similarity measures and optimizers show that our generalized IC method equals or exceeds the performance of the original IC approach. The generalized ESM approach is more reliable than the classic approach as it increases the capture radius of the optimization.