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IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 9 • Date Sept. 2000

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Displaying Results 1 - 13 of 13
  • Editorial

    Publication Year: 2000, Page(s):921 - 922
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    Freely Available from IEEE
  • A handwritten numeral character classification using tolerant rough set

    Publication Year: 2000, Page(s):923 - 937
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1208 KB)

    Proposes a data classification method based on the tolerant rough set that extends the existing equivalent rough set. A similarity measure between two data is described by a distance function of all constituent attributes and they are defined to be tolerant when their similarity measure exceeds a similarity threshold value. The determination of optimal similarity threshold value is very important ... View full abstract»

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  • Robust linear and support vector regression

    Publication Year: 2000, Page(s):950 - 955
    Cited by:  Papers (44)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (208 KB)

    The robust Huber M-estimator, a differentiable cost function that is quadratic for small errors and linear otherwise, is modeled exactly, in the original primal space of the problem, by an easily solvable simple convex quadratic program for both linear and nonlinear support vector estimators. Previous models were significantly more complex or formulated in the dual space and most involved speciali... View full abstract»

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  • Algorithms for defining visual regions-of-interest: comparison with eye fixations

    Publication Year: 2000, Page(s):970 - 982
    Cited by:  Papers (181)  |  Patents (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1180 KB)

    Many machine vision applications, such as compression, pictorial database querying, and image understanding, often need to analyze in detail only a representative subset of the image, which may be arranged into sequences of loci called regions-of-interest (ROIs). We have investigated and developed a methodology that serves to automatically identify such a subset of aROIs (algorithmically detected ... View full abstract»

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  • Recovery of drawing order from single-stroke handwriting images

    Publication Year: 2000, Page(s):938 - 949
    Cited by:  Papers (29)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1056 KB)

    Describes a method to recover a drawing order of a handwritten script from a static 2D image. The script should be written in a single stroke and may include double-traced lines. After the script is scanned in and preprocessed, we apply our recovery method which consists of two phases. In the first phase, we globally analyze the graph constructed from the skeletal image and label the graph by dete... View full abstract»

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  • Adaptive-scale filtering and feature detection using range data

    Publication Year: 2000, Page(s):983 - 991
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2052 KB)

    In edge and corner detection applications, it is typical to examine a single scale without knowing which scale is appropriate for each location in the image. However, many images contain a wide variation in the distance to the scene pixels and, thus, features of the same size can appear at greatly differing scales in the image. We present a method where the scale of the filtering and feature detec... View full abstract»

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  • A spatio-frequency trade-off scale for scale-space filtering

    Publication Year: 2000, Page(s):1050 - 1055
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (320 KB)

    We study implementation issues for spatial convolution filters and their Fourier alternative, with the aim to optimize the accuracy of filter output. We focus on Gaussian scale-space filters and show that there exists a trade-off scale that subdivides the available scale range into two subintervals of equal length. Below this trade-off scale Fourier filtering yields more accurate results than spat... View full abstract»

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  • Model-based brightness constraints: on direct estimation of structure and motion

    Publication Year: 2000, Page(s):992 - 1015
    Cited by:  Papers (28)  |  Patents (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2628 KB)

    We describe a direct method for estimating structure and motion from image intensities of multiple views. We extend the direct methods of Horn and Weldon (1988) to three views. Adding the third view enables us to solve for motion and compute a dense depth map of the scene, directly from image spatio-temporal derivatives in a linear manner without first having to find point correspondences or compu... View full abstract»

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  • Predicting performance of object recognition

    Publication Year: 2000, Page(s):956 - 969
    Cited by:  Papers (17)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (472 KB)

    We present a method for predicting fundamental performance of object recognition. We assume that both scene data and model objects are represented by 2D point features and a data/model match is evaluated using a vote-based criterion. The proposed method considers data distortion factors such as uncertainty, occlusion, and clutter, in addition to model similarity. This is unlike previous approaches... View full abstract»

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  • Shape recovery from equal thickness contours

    Publication Year: 2000, Page(s):1055 - 1061
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (644 KB)

    A unique imaging modality based on equal thickness contours (ETC) has introduced a new opportunity for 3D shape reconstruction from multiple views. These ETC can be generated through an interference between transmitted and diffracted beams. We present a computational framework for representing each view of an object in terms of its object thickness and then integrating these representations into a... View full abstract»

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  • Merging and splitting eigenspace models

    Publication Year: 2000, Page(s):1042 - 1049
    Cited by:  Papers (91)  |  Patents (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (264 KB)

    We present new deterministic methods that, given two eigenspace models-each representing a set of n-dimensional observations-will: 1) merge the models to yield a representation of the union of the sets and 2) split one model from another to represent the difference between the sets. As this is done, we accurately keep track of the mean. Here, we give a theoretical derivation of the methods, empiri... View full abstract»

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  • Mobile robot relocation from echolocation constraints

    Publication Year: 2000, Page(s):1035 - 1041
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (848 KB)

    This paper presents a method for relocation of a mobile robot using sonar data. The process of determining the pose of a mobile robot with respect to a global reference frame in situations where no a priori estimate of the robot's location is available is cast as a problem of searching for correspondences between measurements and an a priori map of the environment. A physically-based sonar sensor ... View full abstract»

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  • Learning and classification of complex dynamics

    Publication Year: 2000, Page(s):1016 - 1034
    Cited by:  Papers (81)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3220 KB)

    Standard, exact techniques based on likelihood maximization are available for learning auto-regressive process models of dynamical processes. The uncertainty of observations obtained from real sensors means that dynamics can be observed only approximately. Learning can still be achieved via “EM-K”-expectation-maximization (EM) based on Kalman filtering. This cannot handle more complex ... View full abstract»

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Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
David A. Forsyth
University of Illinois
e-mail: daf@illinois.edu