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Application of wavelet technique to freeway incident detection

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2003年第3-4期11卷 289-308页

作者： Teng, HL Qi, Y Polytech Univ Urban ITS Ctr Brooklyn NY 11201 USA

This paper presents an application of the wavelet technique to freeway incident detection because wavelet techniques have demonstrated superior performance in detecting changes in signals in electrical engineering. Unlike the existing wavelet incident detection algorithm, where the wavelet technique is utilized to denoise data before the data is input into an algorithm, this paper presents a different approach in the application of the wavelet technique to incident detection. In this approach, the features that are extracted from traffic measurements by using wavelet transformation are directly utilized in detecting changes in traffic flow. It is shown in the paper that the extracted features from traffic measurements in incident conditions are significantly different from those in normal conditions. This characteristic of the wavelet technique was used in developing the wavelet incident detection algorithm in this study. The algorithm was evaluated in comparison with the multi-layer feed-forward neural network, probabilistic neural network, radial basis function neural network, California and low-pass filtering algorithms. The test results indicate that the wavelet incident detection algorithm performs better than other algorithms, demonstrating its potential for practical application. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： freeway incident management incident detection algorithm wavelet application algorithm evaluation neural network models

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Motion estimation algorithms for video compression: evaluation environment and student projects

Motion estimation algorithms for video compression: Evaluati...

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International Conference on Information Technology

作者： Kaminsky, E Hadar, O Ben Gurion Univ Negev Dept Elect & Comp Engn IL-804105 Beer Sheva Israel

ISBN: (纸本)0780377249

This paper suggests a computer simulation environment for analysis of fast motion estimation (ME) algorithms. We present an architecture for algorithm evaluation, ME algorithms, results, of computer simulations, and illustrate the analysis with tables, PSNR plots, and performance plots. The paper also describes multi-criteria evaluation of algorithms. Two evaluation strategies are suggested: (i) a strategy with constraints and (ii) a strategy with "near" Pareto-efficient points. Four basic test video sequences were used. Our algorithm evaluation environment was effectively used as a basis for student projects.

关键词： fast motion estimation (ME) block matching algorithms (BMA) algorithm evaluation multi-criteria analysis computer simulation algorithm evaluation environment student projects

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Consistency of MODIS surface bidirectional reflectance distribution function and albedo retrievals: 1. algorithm performance

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JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 2003年第D5期108卷

作者： Jin, YF Schaaf, CB Gao, F Li, XW Strahler, AH Lucht, W Liang, SL Boston Univ Dept Geog Boston MA 02215 USA Boston Univ Ctr Remote Sensing Boston MA 02215 USA Potsdam Inst Klimafolgenforsch D-14412 Potsdam Germany Univ Maryland Dept Geog College Pk MD 20742 USA Beijing Normal Univ Res Ctr Remote Sensing Beijing 100875 Peoples R China

[1] The first consistent year (November 2000 to November 2001) of global albedo product was produced at 1-km resolution every 16 days from the observations of the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA's Terra spacecraft. We evaluated the quality of the operational albedo retrievals in two ways: (1) by examining the algorithm performance using the product quality assurance (QA) fields (this paper) and (2) by comparing retrieved albedos with those observed at ground stations and by other satellite instruments (in a companion paper). The internal diagnostics of the retrieval algorithm adequately reflect the goodness of the model fit and the random noise amplification in the retrieved albedo. Global QA statistics show that the RossThick-LiSparse-Reciprocal model fits the atmospherically corrected surface reflectances very well, and the random noise amplification factors for white sky albedo and reflectance are generally less than 1.0. Cloud obscuration is the main reason for the activation of the backup magnitude retrieval algorithm. Over the 60degreesS to 60degreesN latitude band, 50% of the land pixels acquire more than six clear looks during 14-29 September 2001, and only 5% of these pixels are inverted with the backup algorithm. The latitude dependence and temporal distribution of the QA fields further demonstrate that the retrieval status mainly follows the pattern of angular sampling determined by cloud climatology and the instrument/orbit characteristics. A case study over the west coast of the United States shows that white sky shortwave albedos retrieved from magnitude inversions agree on average with those from full inversions to within 0.033 in reflectance units and have a slightly lower bias ranging from 0.014 to 0.023. We also explored the effect of residual cloud and aerosol contamination in the atmospherically corrected surface reflectance inputs in another case study over southern Africa. The quality assurance proce

关键词： MODIS bidirectional reflectance distribution function surface albedo algorithm evaluation

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Qualitative evaluation of computer vision algorithms in polar terrains

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ROBOTICS AND AUTONOMOUS SYSTEMS 2002年第2-3期40卷 139-149页

作者： Vandapel, N Chatila, R CNRS LAAS F-31077 Toulouse France

We address the issue of Computer Vision in Antarctica for robot navigation by analysing images collected at Patriot Hills, Antarctica in the Fall of 1998. Conditions produced by polar weather and terrain are unique and challenging for perception equipment and computer vision algorithms. The later aspect will be studied here through the evaluation of a colour segmentation algorithm, a stereo vision algorithm and a feature points detector and tracker algorithm. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： polar robotics navigation algorithm evaluation perception

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Qualitative evaluation of computer vision algorithms in polar terrains

Qualitative evaluation of computer vision algorithms in pola...

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6th International Conference on Intelligent Autonomous Systems (IAS-6)

作者： Vandapel, N Chatila, R CNRS LAAS F-31077 Toulouse France

关键词： polar robotics navigation algorithm evaluation perception

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Parameter optimization for Takagi-Sugeno fuzzy models -: Lessons learnt

Parameter optimization for Takagi-Sugeno fuzzy models -: Les...

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IEEE International Conference on Systems, Man and Cybernetics (SMC)

作者： Männle, M Univ Karlsruhe Inst Comp Design & Fault Tolerance D-76128 Karlsruhe Germany

ISBN: (纸本)0780370872

This article describes an approach to automatically build a Takagi-Su-eno fuzzy model (TSK-model) based on a set of input-output data (system identification). Identifying rule-based fuzzy models consists of two parts: structure modeling, i.e. determining the number of rules and input variables involved respectively, and parameter optimization, i. e. optimizing the rules consequences and the location and steepness of the fuzzy sets. For structure modeling, we investigate several search heuristics, also proposed by Takagi, Sugeno, and Kang in [1, 2, 3] or by Nelles in [4]. In order to find a good model structure, such search heuristics make it necessary to optimize and then evaluate a large number of different candidate models. To be applicable to real world problems, the parameter optimization must be highly efficient. For this, we investigate the use of two gradient descent algorithms: standard gradient descent (backpropagation) and resilient propagation (RPROP) [5, 6]. The combination of a structure search with a fast parameter optimization yields a powerful modeling algorithm that is capable to identify large real world systems. Several preceding publications showed the applicability of TSK fuzzy models to real world problems, e. g. [4, 7, 8]. In this paper we evaluate a number of varieties of TSK-like fuzzy models by performing a nonlinear regression benchmark of 1. Frank [9]. We compare several types of fuzzy models that are constructed as combinations of different fuzzy sets, structuring algorithms, and parameter optimization techniques.

关键词： Takagi-Sugeno fuzzy model nonlinear system identification parameter optimization algorithm evaluation bench-mark

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Identification of chemical components in XPS spectra and images using multivariate statistical analysis methods

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JOURNAL OF ELECTRON SPECTROSCOPY AND RELATED PHENOMENA 2001年第1-3期121卷 33-55页

作者： Artyushkova, K Fulghum, JE Kent State Univ Dept Chem Kent OH 44242 USA

A variety of data analysis methods can be used to enhance the information obtained from a measurement, or to simplify extraction of significant components from large data sets. Much work is needed to improve the quantification and interpretation of XPS spectra and images from complex organics. Multivariate analysis (MVA) is increasingly used for applications in electron spectroscopy to aid the analyst in interpreting the vast amount of information yielded by spectroscopic techniques. In general, the goals of MVA are to determine the number of components present, identify the chemical components, and quantify component concentrations in the mixture. Principal component analysis (PCA) is frequently used to determine the number of mathematical components which describe the data set. These mathematical components must then be related to chemically meaningful components. Various approaches to solve rotational ambiguities of spectral resolution, including local rank method (EFA), pure variables method (Simplisma) and multivariate curve resolution (MCR), are tested in the determination of chemical components from XPS data. Limitations associated with the resolution of a single matrix are shown to be partially or completely overcome when several related matrices are treated together. The test data sets contain XPS images or spectra acquired from blends of poly(vinyl chloride), PVC, and poly(methyl methacrylate), PMMA. The PVC degrades rapidly upon exposure to the X-ray beam. Spectra and images from the blend, acquired as a function of time, provide the multi-dimensional data sets for algorithm evaluation. In addition to spectral resolution, multivariate image analysis methods, such as principal component analysis, are used to extract maps of the pure components from an images-to-spectra data set. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： XPS PVC/PMMA polymer blend multivariate data analysis multivariate curve resolution multivariate image analysis algorithm evaluation

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An objective evaluation of four SAR image segmentation algorithms

An objective evaluation of four SAR image segmentation algor...

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Conference on algorithms for Synthetic Aperture Radar Imagery VIII

作者： Gregga, JB Gustafson, SC Power, GJ AFRL SNAT Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819440779

Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts, automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods. This paper evaluates four SAR image segmentation algorithms by running them on a common set of data and objectively comparing them to each other and to human segmentations. This objective comparison uses a multi-measure approach with a set of master segmentations as ground truth. The measure results are compared to a Human Threshold, which defines the performance of human segmentors compared to the master segmentations. Also, methods that use the multi-measures to determine the best algorithm are developed. These methods show that of the four algorithms, Statistical Curve Evolution produces the best segmentations;however, none of the algorithms are superior to human segmentations. Thus, with the Human Threshold and Statistical Curve Evolution as benchmarks, this paper establishes a new and practical framework for testing SAR image segmentation algorithms.

关键词： SAR image segmentation segmentation measures algorithm evaluation measures metrics

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The FERET evaluation methodology for face-recognition algorithms

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2000年第10期22卷 1090-1104页

作者： Phillips, PJ Moon, H Rizvi, SA Rauss, PJ Natl Inst Stand & Technol Gaithersburg MD 20899 USA Lau Technol Littleton MA 01460 USA CUNY Coll Staten Isl Dept Engn Sci & Phys Staten Isl NY 10314 USA USA Res Lab Adelphi MD 20783 USA

Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial images and the establishment of the FERET tests. To date, 14,126 images from 1,199 individuals are included in the FERET database, which is divided into development and sequestered portions of the database. In September 1996, the FERET program administered the third in a series of FERET face-recognition tests. The primary objectives of the third test were to 1) assess the slate of the art, 2) identify future areas of research, and 3) measure algorithm performance.

关键词： face recognition algorithm evaluation FERET database

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evaluation framework for ATR algorithms

Evaluation framework for ATR algorithms

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9th Conference on Automatic Target Recognition

作者： Fries, S Klausmann, P Jäger, U Saur, G Willersinn, D Hofele, G Thönnessen, U FhG Inst Informat & Datenverarbeitung D-76131 Karlsruhe Germany

ISBN: (纸本)0819431923

This contribution presents a comprehensive framework for algorithm evaluation. When we speak of evaluation, we have in mind that first the performance of an algorithm is measured and then the measured performance is assessed with regard to a given application. The performance assessment is done by applying an assessment function that uses desired values for the performance measures and weighting factors giving the importance of each measure, thus considering the application-specific requirements. The algorithm evaluation's goal is to verify the specification of an algorithm. This specification is mainly given by the definition of the input data and the expected output data, both of which are determined by the application. Prior to the evaluation process the algorithm specification has to be laid down by analyzing the application in order to deduce its requirements as well as by defining the application relevant data sets. To organize this sequence of preparatory steps and to formalize the accomplishment of the evaluation we have developed a S-phase approach, consisting of the definition phase, the tuning phase, and the evaluation phase. An extensive software toolbox has been developed to support the evaluation process.

关键词： ATR algorithm evaluation assessment function figure of merit evaluation software

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