The paper presents a new algorithm for parametric image alignment which when given any local match measure applies global estimation directly to the lo cal match measure data without rst going through an intermediate step of local ow estimation This algo rithm can be applied to any local match measure such as correlation normalized correlation squared or ab solute brightness di erences statisti...

A desire with iterative optimization techniques is that the algorithm reaches the global optimum rather than get stranded at a local optimum value. In this paper, we examine the theoretical and numerical global convergence properties of a certain “gradient free” stochastic approximation algorithm called “SPSA,” that has performed well in complex optimization problems. We establish two theorems ...

In the past, new global illumination algorithms have usually been designed as a single module that was responsible for the simulation of all aspects of illumination in a scene. A recently developed alternative is the design of small and specialized algorithms (lighting operators) together with an infrastructure for creating more complex algorithms by connecting these building blocks – the Light...

In this paper we present a modified BFGS algorithm for unconstrained optimization. The BFGS algorithm updates an approximate Hessian which satisfies the most recent quasi-Newton equation. The quasi-Newton condition can be interpreted as the interpolation condition that the gradient value of the local quadratic model matches that of the objective function at the previous iterate. Our modified al...

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can ...

Sparse representation model adopts an image patch as a linear combination of a few atoms chosen out from an overcomplete dictionary, and they have shown promising results in various image restoration applications. Gradient feature is important structure information in image processing. Their combination is not sensitive to noise, which can improve and enhance the accuracy of similarity measure,...

A new algorithm is presented to compute both one dimensional stable and unstable manifolds of planar maps. It is proved that the gradient of the global manifold can be predicted by the known points on the manifold with a gradient prediction scheme and it can be used to locate the image or preimage of the new point quickly. The performance of the algorithm is demonstrated with hyper chaotic Lore...

The Horn-Schunk algorithm (HS) is one of the classical algorithms in optical flow due to its reasonable performance and simplicity of the algorithm. This article presents in detail the process of the HS algorithm and its step by step coding in MATLAB ® . The HS algorithm is a technique used to identify the image velocity or motion vector based on Spatial Temporal Gradient Technique which comput...