采用多尺度掩模消除干扰的反向组合算法

反向组合算法是最有效的图像对齐算法之一,但该算法抗干扰能力差.当输入图像部分被遮挡时,图像对齐效果变差.针对该问题,我们提出一种采用多尺度掩模消除干扰的反向组合算法.该算法采用自适应的方法设置初始掩模,再通过迭代判断和逐层分块来细化初始掩模,使得掩模能准确地设置在干扰区域上.实验结果表明,该算法既保留了原反向组合算法的优点,又提高了算法抗干扰的能力,使得反向组合算法能在更复杂的环境下进行图像对齐.     

AAM反向合成匹配算法及其性能分析

介绍了一种基于反向合成图像对齐算法的AAM匹配算法。首先对反向合成算法的内容及其在AAM匹配过程中需要注意的问题进行了阐述,然后通过实验,分别应用反向合成算法和原始AAM匹配算法对一定数量的图像进行匹配,验证了反向合成算法的有效性。     

Active Appearance Models Revisited

Active Appearance Models (AAMs) and the closely related concepts of Morphable Models and Active Blobs are generative models of a certain visual phenomenon. Although linear in both shape and appearance, overall, AAMs are nonlinear parametric models in terms of the pixel intensities. Fitting an AAM to an image consists of minimising the error between the input image and the closest model instance; i.e. solving a nonlinear optimisation problem. We propose an efficient fitting algorithm for AAMs based on the inverse compositional image alignment algorithm. We show that the effects of appearance variation during fitting can be precomputed (projected out) using this algorithm and how it can be extended to include a global shape normalising warp, typically a 2D similarity transformation. We evaluate our algorithm to determine which of its novel aspects improve AAM fitting performance.Supplementary material to this paper is available in electronic form at http://dx.doi.org/10.1023/B:VISI.0000029666.37597.d3     

基于局部指向性的反向合成图像对齐算法

传统的反向合成图像对齐算法比较的是模板图像与输入图像之间的像素值。该方法容易受到图像中光照变化的影响，从而导致收敛性变差甚至发散。根据局部指向性对光照变化不敏感的特性，提出了一种新的反向合成图像对齐算法——反向合成梯度算法。由于局部指向性的计算在本质上是图像梯度的计算，因此采用几种不同的梯度算子来计算局部指向性。通过实验，验证了反向合成梯度算法能够有效克服图像中光照变化的影响，同时比较了不同算子在不同光照下对反向合成梯度算法的影响。     

Tool integration for flexible simulation of distributed algorithms

Over the last two decades, considerable research has been done in distributed operating systems, which can be attributed to faster processors and better communication technologies. A distributed operating system requires distributed algorithms to provide basic operating system functionality like mutual exclusion, deadlock detection, etc. A number of such algorithms have been proposed in the literature. Traditionally, these distributed algorithms have been presented in a theoretical way, with limited attempts to simulate actual working models. This paper discusses our experience in simulating distributed algorithms with the aid of some existing tools, including OPNET and Xplot. We discuss our efforts to define a basic model‐based framework for rapid simulation and visualization, and illustrate how we used this framework to evaluate some classic algorithms. We have also shown how the performance of different algorithms can be compared based on some collected statistics. To keep the focus of this paper on the approach itself, and our experience with tool integration, we only discuss some relatively simple models. Yet, the approach can be applied to more complex algorithm specifications. Copyright © 2001 John Wiley & Sons, Ltd.     

New Algorithms for Disk Scheduling

Abstract. Processor speed and memory capacity are increasing several times faster than disk speed. This disparity suggests that disk I/ O performance could become an important bottleneck. Methods are needed for using disks more efficiently. Past analysis of disk scheduling algorithms has largely been experimental and little attempt has been made to develop algorithms with provable performance guarantees. We consider the following disk scheduling problem. Given a set of requests on a computer disk and a convex reachability function that determines how fast the disk head travels between tracks, our goal is to schedule the disk head so that it services all the requests in the shortest time possible. We present a 3/2 -approximation algorithm (with a constant additive term). For the special case in which the reachability function is linear we present an optimal polynomial-time solution. The disk scheduling problem is related to the special case of the Asymmetric Traveling Salesman Problem with the triangle inequality (ATSP-Δ ) in which all distances are either 0 or some constant α . We show how to find the optimal tour in polynomial time and describe how this gives another approximation algorithm for the disk scheduling problem. Finally we consider the on-line version of the problem in which uniformly distributed requests arrive over time. We present an algorithm related to the above ATSP-Δ .     

Parametric image alignment using enhanced correlation coefficient maximization

In this work we propose the use of a modified version of the correlation coefficient as a performance criterion for the image alignment problem. The proposed modification has the desirable characteristic of being invariant with respect to photometric distortions. Since the resulting similarity measure is a nonlinear function of the warp parameters, we develop two iterative schemes for its maximization, one based on the forward additive approach and the second on the inverse compositional method. As it is customary in iterative optimization, in each iteration the nonlinear objective function is approximated by an alternative expression for which the corresponding optimization is simple. In our case we propose an efficient approximation that leads to a closed form solution (per iteration) which is of low computational complexity, the latter property being particularly strong in our inverse version. The proposed schemes are tested against the Forward Additive Lucas-Kanade and the Simultaneous Inverse Compositional algorithm through simulations. Under noisy conditions and photometric distortions our forward version achieves more accurate alignments and exhibits faster convergence whereas our inverse version has similar performance as the Simultaneous Inverse Compositional algorithm but at a lower computational complexity.     

一种非线性逆扩散图像增强算法

针对传统图像增强算法无法同时消除噪声和保持纹理的不足，从线性逆扩散的基本原理出发，提出了非线性逆扩散图像增强算法的原则，给出了适合的扩散系数。试验结果表明本算法有效地增强了图像，消除了图像中的噪声，能够保留图像中的细节纹理。     

Algorithms for a Class of Isotonic Regression Problems

The isotonic regression problem has applications in statistics, operations research, and image processing. In this paper a general framework for the isotonic regression algorithm is proposed. Under this framework, we discuss the isotonic regression problem in the case where the directed graph specifying the order restriction is a directed tree with n vertices. A new algorithm is presented for this case, which can be regarded as a generalization of the PAV algorithm of Ayer et al. Using a simple tree structure such as the binomial heap, the algorithm can be implemented in O(n log n) time, improving the previously best known O(n ² ) time algorithm. We also present linear time algorithms for special cases where the directed graph is a path or a star. Received September 2, 1997; revised January 2, 1998, and February 16, 1998.     

A robust template tracking algorithm with weighted active drift correction

In this paper, we propose a novel algorithm for object template tracking and its drift correction. It can prevent the tracking drift effectively, and save the time of an additional correction tracking. In our algorithm, the total energy function consists of two terms: the tracking term and the drift correction term. We minimize the total energy function synchronously for template tracking and weighted active drift correction. The minimization of the active drift correction term is achieved by the inverse compositional algorithm with a weighted L2 norm, which is incorporated into traditional affine image alignment (AIA) algorithm. Its weights can be adaptively updated for each template. For diminishing the accumulative error in tracking, we design a new template update strategy that chooses a new template with the lowest matching error. Finally, we will present various experimental results that validate our algorithm. These results also show that our algorithm achieves better performance than the inverse compositional algorithm for drift correction.