A Bayesian, exemplar-based approach to hierarchical shape matching

This paper presents a novel probabilistic approach to hierarchical, exemplar-based shape matching. No feature correspondence is needed among exemplars, just a suitable pairwise similarity measure. The approach uses a template tree to efficiently represent and match the variety of shape exemplars. The tree is generated offline by a bottom-up clustering approach using stochastic optimization. Online matching involves a simultaneous coarse-to-fine approach over the template tree and over the transformation parameters. The main contribution of this paper is a Bayesian model to estimate the a posteriori probability of the object class, after a certain match at a node of the tree. This model takes into account object scale and saliency and allows for a principled setting of the matching thresholds such that unpromising paths in the tree traversal process are eliminated early on. The proposed approach was tested in a variety of application domains. Here, results are presented on one of the more challenging domains: real-time pedestrian detection from a moving vehicle. A significant speed-up is obtained when comparing the proposed probabilistic matching approach with a manually tuned nonprobabilistic variant, both utilizing the same template tree structure.     

A novel hierarchical fingerprint matching approach

Fingerprint matching is an important and essential step in automated fingerprint recognition systems (AFRSs). The noise and distortion of captured fingerprints and the inaccurate of extracted features make fingerprint matching a very difficult problem. With the advent of high-resolution fingerprint imaging techniques and the increasing demand for high security, sweat pores have been recently attracting increasing attention in automatic fingerprint recognition. Therefore, this paper takes fingerprint pore matching as an example to show the robustness of our proposed matching method to the errors caused by the fingerprint representation. This method directly matches pores in fingerprints by adopting a coarse-to-fine strategy. In the coarse matching step, a tangent distance and sparse representation-based matching method (denoted as TD-Sparse) is proposed to compare pores in the template and test fingerprint images and establish one-to-many pore correspondences between them. The proposed TD-Sparse method is robust to noise and distortions in fingerprint images. In the fine matching step, false pore correspondences are further excluded by a weighted RANdom SAmple Consensus (WRANSAC) algorithm in which the weights of pore correspondences are determined based on the dis-similarity between the pores in the correspondences. The experimental results on two databases of high-resolution fingerprints demonstrate that the proposed method can achieve much higher recognition accuracy compared with other state-of-the-art pore matching methods.     

A hierarchical approach to instruction-level parallelization

In this paper we extend Percolation Scheduling (PS) to navigate through a hierarchical version of the Control Flow Graph (CFG) representation of a VLIW program. This extension retains the completeness of PS by allowing the “normal” PS transformations to be applied incrementally between adjacent instructions but also enablesnonincremental code motions across arbitrarily large single-entry/single-exit regions of code in constant time. Such nonincremental transformations eliminate the useless code explosions that would otherwise be caused by using incremental transformations to move operations through regions containing multiple control paths and, in conjunction with the hierarchical representation of the CFG, provide a framework for trading offuseful code explosions for increases in parallelism. Simulation results comparing nonincremental with incremental PS are presented. This work was supported in part by NSF Grant CCR8704367 and ONR Grant N0001486K0215.     

Computer image generation for flight simulators: the Gabor approach

A formalism for image representation in the combined frequency-position space is presented using the generalized Gabor approach. This approach uses elementary functions to which the human visual system is particularly sensitive and which are efficient for the analysis and synthesis of visual imagery. The formalism is also compatible with the implementation of a variable resolution system wherein image information is nonuniformly distributed across the visual field in accordance with the human visual system's ability to process it. When used with a gaze-slaved visual display system, imagery generated using the techniques described here affords a combination of high resolution and wide field-of-view. This combination is particularly important in high-fidelity, computergenerated, visual environments as required, for instance, in flight simulators.     

A hierarchical/relational approach to modeling

We describe a hierarchical/relational approach to math programming modeling. The approach transforms free-form generic modeling constructs into linear and nonlinear models which are independent of end-user data structures. The underlying relationships with graph-based interfaces and the inherent aggregation/disaggregation capabilities of the approach are also discussed.The modeling approach will be illustrated with several process industry applications including distribution planning, operations planning, and production scheduling.     

A regularized pan-sharpening approach based on self-similarity and Gabor prior

In this article, we propose a new regularization-based approach for pan-sharpening based on the concepts of self-similarity and Gabor prior. The given low spatial resolution (LR) and high spectral resolution multi-spectral (MS) image is modelled as degraded and noisy version of the unknown high spatial resolution (HR) version. Since this problem is ill-posed, we use regularization to obtain the final solution. In the proposed method, we first obtain an initial HR approximation of the unknown pan-sharpened image using self-similarity and sparse representation (SR) theory. Using self-similarity, we obtain the HR patches from the given LR observation by searching for matching patches in its coarser resolution, thereby obtaining LR–HR pairs. An SR framework is used to obtain the patch pairs for which no matches are available for the patches in LR observation. The entire set of matched HR patches constitutes initial HR approximation (initial estimate) to the final pan-sharpened image which is used to estimate the degradation matrix as used in our model. A regularization framework is then used to obtain the final solution in which we propose to use a new prior which we refer as Gabor prior that extracts the bandpass details from the registered panchromatic (Pan) image. In addition, we also include Markov random field (MRF) smoothness prior that preserves the smoothness in the final pan-sharpened image. MRF parameter is derived using the initial estimate image. The final cost function consists of data fitting term and two prior terms corresponding to Gabor and MRF. Since the derived cost function is convex, simple gradient-based method is used to obtain the final solution. The efficacy of the proposed method is evaluated by conducting the experiments on degraded as well as on un-degraded datasets of three different satellites, i.e., Ikonos-2, Quickbird, and Worldview-2. The results are compared on the basis of traditional measures as well as recently proposed quality with no reference (QNR) measure, which does not require the reference image.     

基于局部中频Gabor滤波器组的人脸识别

针对传统Gabor滤波器组在人脸识别过程中特征提取时间长、计算量大的问题,提出一种利用局部Gabor滤波器组进行人脸图像中频特征提取的方法.选择中频带的Gabor滤波器构造局部中频Gabor滤波器组;提取局部Gabor中频特征;采用线性判别分析法(linear discriminate analysis,LDA)进一步提取Fisher特征,得到图像的Gabor+ Fisher特征,利用最近邻法进行人脸图像识别.基于ORL和AR人脸库的实验结果表明,基于此局部Gabor滤波器组的人脸识别方法较传统的Gabor特征提取方法降低了40％的特征维数,加快了特征提取速度,提高了人脸识别率.     

A hierarchical multiple-view approach to three-dimensional objectrecognition

A hierarchical approach is proposed for solving the surface and vertex correspondence problems in multiple-view-based 3D object-recognition systems. The proposed scheme is a coarse-to-fine search process, and a Hopfield network is used at each stage. Compared with conventional object-matching schemes, the proposed technique provides a more general and compact formulation of the problem and a solution more suitable for parallel implementation. At the coarse search stage, the surface matching scores between the input image and each object model in the database are computed through a Hopfield network and are used to select the candidates for further consideration. At the fine search stage, the object models selected from the previous stage are fed into another Hopfield network for vertex matching. The object model that has the best surface and vertex correspondences with the input image is finally singled out as the best matched model. Experimental results are reported using both synthetic and real range images to corroborate the proposed theory.     

A hierarchical approach to multi-class fuzzy classifiers

In this paper we present a hierarchical approach for generating fuzzy rules directly from data in a simple and effective way. The fuzzy classifier results from the union of fuzzy systems, employing the Wang and Mendel algorithm, built on input regions increasingly smaller, according to a multi-level grid-like partition. Key parameters of the proposed method are optimized by means of a genetic algorithm. Only the necessary partitions are built, in order to guarantee high interpretability and to avoid the explosion of the number of rules as the hierarchical level increases. We apply our method to real-world data collected from a photovoltaic (PV) installation so as to linguistically describe how the temperature of the PV panel and the irradiation relate to the class (low, medium, high) of the energy produced by the panel. The obtained mean and maximum classification percentages on 30 repetitions of the experiment are 97.38% and 97.91%, respectively. We also apply our method to the classification of some well-known benchmark datasets and show how the achieved results compare favourably with those obtained by other authors using different techniques.     

A hierarchical approach to parallel multiquery scheduling

There has been a good deal of progress made recently toward the efficient parallelization of individual phases of single queries in multiprocessor database systems. In this paper we devise and experimentally evaluate a number of scheduling algorithms designed to handle multiple parallel queries. (Scheduling in this context implies the determination of both processor allotments and temporal processor assignments to individual queries and query phases.) One of these algorithms performs the best in our experiments. This algorithm is hierarchical in nature: In the first phase, a good quality precedence based schedule is created for each individual query and each possible number of processors. This component employs dynamic programming. In the second phase, the results of the first phase are used to create an overall schedule of the full set of queries. This component is based on previously published work on nonprecedence-based malleable scheduling. Even though the problem we are considering is NP-hard in the strong sense, the multiple query schedules generated by our hierarchical algorithm are seen experimentally to achieve high quality results     

一种协调目标信息系统中决策规则的融合方法

决策规则获取是目标信息系统中的一个重要研究内容。引入了一种集合向量空间上的加权包含度,并基于该包含度提出了一种协调目标信息系统中决策规则的融合方法,可以得到全部决策规则,实例表明了该方法的有效性。     

Automated merging of conflicting knowledge bases,using a consistent,majority-rule approach with knowledge-form maintenance

This paper discusses an automated process of merging conflicting information from disparate sources into a combined knowledge base. The algorithm provided generates a mathematically consistent, majority-rule merging by assigning weights to the various sources. The sources may be either conflicting portions of a single knowledge base or multiple knowledge bases. Particular attention is paid to maintaining the original rule format of the knowledge, while ensuring logical equivalence. This preservation of rule format keeps the knowledge in a more intuitive implication form as opposed to a collection of clauses with many possible logical roots. It also facilitates tracking using the support for each deductive result so that final knowledge in rule form can be ascribed back to original experts. As the approach is fairly involved mathematically, an automated procedure is developed.     

An approach for enhancing fingerprint images using adaptive Gabor filter parameters

This work proposes a technique to enhance fingerprint images through the Gabor filter with adaptive parameters. Firstly, the average ridge and valley of each region as well as their direction are evaluated by a specific directional field algorithm. Secondly, since the filter orientation and the frequency parameters vary according to the fingerprint area, the fingerprint topological structure is enhanced by the Gabor filter with adaptive parameters. Finally, experimental tests show accurate final results for the matching step of an on-line recognition process. The text was submitted by the authors in English. Sanderson L. Gonzaga de Oliveira graduated from the Pontificia Universidade Catolica do Parana in 1996 and received his M.Sc. degree in 2004. Currently, he is a doctoral candidate in the Universidade Federal Fluminense, Brazil. His research interests include Image Processing and Computer Modeling. Author of 15 papers. A. Conci is a Dr.Sc. professor in the Department of Computer Science in Universidade Federal Fluminense. Her research interests include Biomechanics, Applications of Computer Vision, and Image Processing. F. M. Viola received his B.Sc. in Computer Science in 1999 and his M.Sc. at Universidade Federal Fluminense in 2006. His research interests include Biometrics and Image Processing.     

An approach to evaluation of hierarchical systems performance

An approach to assessment of performance of hierarchical systems with simple subordination is developed with regard to moment characteristics of sequences of random sums. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 70–79, July–August, 2000.     

Reliability model for hierarchical systems: Regenerative approach

Most of real technical systems and biological objects with sufficiently high organization are complex hierarchical partially controllable systems. In the paper for modeling and analysis of reliability of such systems the method of decomposable semi-regenerative processes is used. A simple example illustrates our approach.     

Tracking approach in hierarchical optimization of large-scale systems

A synthesis of hierarchical optimization methods for large-scale systems formed by interconnected units is presented using the tracking approach. A general decomposition-coordination structure combining various coordination strategies is proposed. The resulting algorithm, which is very efficient, convivial, and applicable to a large class of problems, is illustrated by a numerical example.     

An integrated hierarchical programming approach for industrial planning

This paper describes of prototype of a microcomputer implementation of an integrated multicriteria expert support system (MCESS). The system is an interactive, comprehensive, and easy to use tool to support the manager in project selection and resource allocation. The MCESS combines the capabilities of goal programming, the analytic hierarchy process, net present value analysis, and a spreadsheet.

The literature on modeling with spreadsheets and on software integration is reviewed. Goal programming, a multicriteria decision making technique is described and the analytic hierarchy process is shown to be able to overcome some of its limitations. The structure of the MCESS is described. An illustration of its use in industrial planning is presented.     

A decision theoretic approach to hierarchical classifier design

The design of tree classifiers is considered from the statistical point of view. The procedure for calculating the a posteriori probabilities is decomposed into a sequence of steps. In every step the a posteriori probabilities for a certain subtask of the given pattern recognition task are calculated. The resulting tree classifier realizes a soft-decision strategy in contrast to the hard-decision strategy of the conventional decision tree. At the different nonterminal nodes, mean square polynomial classifiers are applied having the property of estimating the desired a posteriori probabilities together with an integrated feature selection capability.     

A lidar-based hierarchical approach for assessing MODIS fPAR

The purpose of this study was to estimate the fraction of photosynthetically active radiation absorbed by the canopy (fPAR) from point measurements to airborne lidar for hierarchical scaling up and assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) fPAR product within a “medium-sized” (7 km × 18 km) watershed. Nine sites across Canada, containing one or more (of 11) distinct species types and age classes at varying stages of regeneration and seasonal phenology were examined using a combination of discrete pulse airborne scanning Light Detection And Ranging (lidar) and coincident analog and digital hemispherical photography (HP). Estimates of fPAR were first compared using three methods: PAR radiation sensors, HP, and airborne lidar. HP provided reasonable estimates of fPAR when compared with radiation sensors. A simplified fractional canopy cover ratio from lidar based on the number of within canopy returns to the total number of returns was then compared with fPAR estimated from HP at 486 geographically registered measurement locations. The return ratio fractional cover method from lidar compared well with HP-derived fPAR (coefficient of determination = 0.72, RMSE = 0.11), despite varying the lidar survey configurations, canopy structural characteristics, seasonal phenologies, and possible slight inaccuracies in location using handheld GPS at some sites. Lidar-derived fractional cover estimates of fPAR were ～ 10% larger than those obtained using HP (after removing wood components), indicating that lidar likely provides a more realistic estimate of fPAR than HP when compared with radiation sensors. Finally, fPAR derived from lidar fractional cover was modelled at 1 m resolution and averaged over 99 1 km areas for comparison with MODIS fPAR. The following study is one of the first to scale between plot measurements and MODIS pixels using airborne lidar.