Fast surface interpolation using hierarchical basis functions

An alternative to multigrid relaxation that is much easier to implement and more generally applicable is presented. Conjugate gradient descent is used in conjunction with a hierarchical (multiresolution) set of basis functions. The resultant algorithm uses a pyramid to smooth the residual vector before the direction is computed. Simulation results showing the speed of convergence and its dependence on the choice of interpolator, the number of smoothing levels, and other factors are presented. The relationship of this approach to other multiresolution relaxation and representation schemes is also discussed     

Fast pattern recognition using normalized grey-scale correlation in a pyramid image representation

The ability to quickly locate one or more instances of a model in a grey scale image is of importance to industry. The recognition/localization must be fast and accurate. In this paper we present an algorithm which incorporates normalized correlation into a pyramid image representation structure to perform fast recognition and localization. The algorithm employs an estimate of the gradient of the correlation surface to perform a steepest descent search. Test results are given detailing search time by target size, effect of rotation and scale changes on performance, and accuracy of the subpixel localization algorithm used in the algorithm. Finally, results are given for searches on real images with perspective distortion and the addition of Gaussian noise.     

Efficient normalized cross correlation calculation method for stereo vision based robot navigation

Stereo vision systems are widely used for autonomous robot navigation. Most of them apply local window based methods for real-time purposes. Normalized cross correlation (NCC) is notorious for its high computational cost, though it is robust to different illumination conditions between two cameras. It is rarely used in real-time stereo vision systems. This paper proposes an efficient normalized cross correlation calculation method based on the integral image technique. Its computational complexity has no relationship to the size of the matching window. Experimental results show that our algorithm can generate the same results as traditional normalized cross correlation with a much lower computational cost. Our algorithm is suitable for planet rover navigation.     

New faster normalized neural networks for sub-matrix detection using cross correlation in the frequency domain and matrix decomposition

Neural networks have shown good results for detecting a certain pattern in a given image. In this paper, faster neural networks for pattern detection are presented. Such processors are designed based on cross correlation in the frequency domain between the input matrix and the input weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the detection process. The principle of divide and conquer strategy is applied through matrix decomposition. Each matrix is divided into smaller in size submatrices and then each one is tested separately by using a single faster neural processor. Furthermore, faster pattern detection is obtained by using parallel processing techniques to test the resulting submatrices at the same time using the same number of faster neural networks. In contrast to faster neural networks, the speed up ratio is increased with the size of the input matrix when using faster neural networks and matrix decomposition. Moreover, the problem of local submatrix normalization in the frequency domain is solved. The effect of matrix normalization on the speed up ratio of pattern detection is discussed. Simulation results show that local submatrix normalization through weight normalization is faster than submatrix normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.     

核磁共振图像归一化互相关非局部自适应去噪

为了更好地去除核磁共振(MR)图像中莱斯(Rician)分布的噪声,首先提出使用图像局部归一化互相关(NCC)作为几何结构相似性的一个表征,对传统非局部算法中使用灰度计算像素相似性权值的方法进行有效补充;然后,将改进方法分别应用于非局部均值算法和非局部最小线性均方误差估计算法,并根据局部信噪比(SNR)动态自适应地计算非局部算法中待滤波像素自身的加权值或者像素之间相似性阈值,达到对核磁图像自适应降噪的目的。实验结果表明,该算法可以更好地抑制核磁图像中的莱斯噪声,有效保留图像中细节信息,对核磁共振图像进一步的分析研究以及应用于临床诊断等具有非常重要的应用价值。     

Fast evaluation of radial basis functions: I

This paper describes some new techniques for the rapid evaluation and fitting of radial basic functions. The techniques are based on the hierarchical and multipole expansions recently introduced by several authors for the calculation of many-body potentials. Consider in particular the N term thin-plate spline, s(x) = Σ_j=1^N d_jφ(x−x_j), where φ(u) = |u|²log|u|, in 2-dimensions. The direct evaluation of s at a single extra point requires an extra O(N) operations. This paper shows that, with judicious use of series expansions, the incremental cost of evaluating s(x) to within precision ε, can be cut to O(1+|log ε|) operations. In particular, if A is the interpolation matrix, a_i,j = φ(x_i−x_j, the technique allows computation of the matrix-vector product Ad in O(N), rather than the previously required O(N²) operations, and using only O(N) storage. Fast, storage-efficient, computation of this matrix-vector product makes pre-conditioned conjugate-gradient methods very attractive as solvers of the interpolation equations, Ad = y, when N is large.     

Fast algorithms for estimating the correlation functions of large signals

A fast algorithm is proposed for estimating the auto- and cross-correlation functions of a large signal. The algorithm is based on the sectioning method by the fast Fourier transform. We determine the optimal length of the portion of data read from external memory into RAM which achieves T_min—a minimum processing time. An estimate of T_min is obtained.Translated from Kibernetika, No. 3, pp. 78–81, May–June, 1991.     

Fast object tracking using adaptive block matching

We propose a fast object tracking algorithm that predicts the object contour using motion vector information. The segmentation step common in region-based tracking methods is avoided, except for the initialization of the object. Tracking is achieved by predicting the object boundary using block motion vectors followed by updating the contour using occlusions/disocclusion detection. An adaptive block-based approach has been used for estimating motion between frames. An efficient modulation scheme is used to control the gap between frames used for motion estimation. The algorithm for detecting disocclusion proceeds in two steps. First, uncovered regions are estimated from the displaced frame difference. These uncovered regions are classified into actual disocclusions and false alarms by observing the motion characteristics of uncovered regions. Occlusion and disocclusion are considered as dual events and this relationship is explained in detail. The algorithm for detecting occlusion is developed by modifying the disocclusion detection algorithm in accordance with the duality principle. The overall tracking algorithm is computationally superior to existing region-based methods for object tracking. The immediate applications of the proposed tracking algorithm are video compression using MPEG-4 and content retrieval based on standards like H.264. Preliminary simulation results demonstrate the performance of the proposed algorithm.     

Robot formation motion planning using Fast Marching

This paper presents the application of the Voronoi Fast Marching (VFM) method to path planning of mobile formation robots. The VFM method uses the propagation of a wave (Fast Marching) operating on the world model to determine a motion plan over a viscosity map (similar to the refraction index in optics) extracted from the updated map model. The computational efficiency of the method allows the planner to operate at high rate sensor frequencies. This method allows us to maintain good response time and smooth and safe planned trajectories. The navigation function can be classified as a type of potential field, but it has no local minima, it is complete (it finds the solution path if it exists) and it has a complexity of order n(O(n)), where n is the number of cells in the environment map. The results presented in this paper show how the proposed method behaves with mobile robot formations and generates trajectories of good quality without problems of local minima when the formation encounters non-convex obstacles.     

Visual tracking for UAV using adaptive spatio-temporal regularized correlation filters

Applied Intelligence - The advance of visual tracking has provided unmanned aerial vehicle (UAV) with the intriguing capability for various practical applications. With promising performance and...     

Efficient tracking using a robust motion estimation technique

Camera based supervision is a critical part of event detection and analysis applications. However, visual tracking still remains one of the biggest challenges in the area of computer vision, although it has been extensively discussed during in the previous years. In this paper we propose a robust tracking approach based on object flow, which is a motion model for estimating both the displacement and the direction of an object of interest. In addition, an observation model that utilizes a generative prior is adopted to tackle the pitfalls that derive from the appearance changes of the object under study. The efficiency of our technique is demonstrated using sequences captured in a complex industrial environment. The experimental results show that the proposed algorithm is sound, yielding improved performance in comparison with other tracking approaches.     

Genetic CONDENSATION for motion tracking

Tracking serves as a means to prepare data for pose estimation and action recognition. The CONDENSATION algorithm is a conditional density propagation method for motion tracking. This algorithm combines factored sampling with learned dynamic models to propagate an entire probability distributes for object position and shape over time. It can accomplish highly robust tracking of object motion. However, it usually requires a large number of samples to ensure a fair maximum likelihood estimation of the current state. In this paper, we use the mutation and crossover operators of the genetic algorithm to find appropriate samples. With this approach, we are able to improve robustness, accuracy and flexibility in CONDENSATION for visual tracking.     

A versatile approach for stochastic correlation using hyperbolic functions

It is well known that the correlation between financial products or financial institutions, e.g. plays an essential role in pricing and evaluation of financial derivatives. Using simply a constant or deterministic correlation may lead to correlation risk, since market observations give evidence that correlation is not a deterministic quantity. In this work, we propose a new approach to model the correlation as a hyperbolic function of a stochastic process. Our general approach provides a stochastic correlation which is much more realistic to model real- world phenomena and could be used in many financial application fields. Furthermore, it is very flexible: any mean-reverting process (with positive and negative values) can be regarded and no additional parameter restrictions appear which simplifies the calibration procedure. As an example, we compute the price of a Quanto applying our new approach. Using our numerical results we discuss concisely the effect of considering stochastic correlation on pricing the Quanto.     

Fast template matching using bounded partial correlation

This paper describes a novel, fast template-matching technique, referred to as bounded partial correlation (BPC), based on the normalised cross-correlation (NCC) function. The technique consists in checking at each search position a suitable elimination condition relying on the evaluation of an upper-bound for the NCC function. The check allows for rapidly skipping the positions that cannot provide a better degree of match with respect to the current best-matching one. The upper-bounding function incorporates partial information from the actual cross-correlation function and can be calculated very efficiently using a recursive scheme. We show also a simple improvement to the basic BPC formulation that provides additional computational benefits and renders the technique more robust with respect to the parameters choice. Received: 2 November 2000 / Accepted: 25 July 2001 Correspondence to: L. Di Stefano     

基于互相关边界特性和图像积分的快速模板匹配算法

基于归一化算法求解相似度原理,提出了综合利用互相关的边界条件和图像积分计算相似度的快速算法,在不降低匹配精度的前提下较大地提高了匹配速度。计算相似度时,归一化算法需要计算各位置的自相关值和互相关值,本算法先只计算自相关值,再利用Holder不等式原理,结合给定的边界阈值,剔除不满足条件的位置,减少其对应的互相关值计算。应用图像的积分进行匹配在于整个图像的积分可以在匹配之前进行计算,而在匹配过程中每一个子区域的自相关可以通过图像积分快速求得。本算法已在焊线机芯片识别系统中应用,结果表明该算法匹配的速度快而又不降低匹配精度,具有实际应用价值。     

Rapid iterative method for electronic-structure eigenproblems using localised basis functions

Eigenproblems resulting from the use of localised basis functions (typically Gaussian or Slater type orbitals) in density functional electronic-structure calculations are often solved using direct linear algebra. A full implementation is presented built around an iterative method known as ‘residual minimisation—direct inversion of the iterative subspace’ (RM-DIIS) to be used to solve many similar eigenproblems in a self-consistency cycle. The method is more efficient than direct methods and exhibits superior scaling on parallel supercomputers.     

Non-linear systems identification using radial basis functions

This paper investigates the identification of discrete-time non-linear systems using radial basis functions. A forward regression algorithm based on an orthogonal decomposition of the regression matrix is employed to select a suitable set of radial basis function centers from a large number of possible candidates and this provides, for the first time, fully automatic selection procedure for identifying parsimonious radial basis function models of structure-unknown non-linear systems. The relationship between neural networks and radial basis functions is discussed and the application of the algorithms to real data is included to demonstrate the effectiveness of this approach.