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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 2 • Date Feb 1998

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Displaying Results 1 - 12 of 12
  • Characterization of neuropathological shape deformations

    Publication Year: 1998 , Page(s): 97 - 112
    Cited by:  Papers (26)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1500 KB)  

    We present a framework for analyzing the shape deformation of structures within the human brain. A mathematical model is developed describing the deformation of any brain structure whose shape is affected by both gross and detailed physical processes. Using our technique, the total shape deformation is decomposed into analytic modes of variation obtained from finite element modeling, and statistic... View full abstract»

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  • Closed-loop object recognition using reinforcement learning

    Publication Year: 1998 , Page(s): 139 - 154
    Cited by:  Papers (41)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (3380 KB)  

    Current computer vision systems whose basic methodology is open-loop or filter type typically use image segmentation followed by object recognition algorithms. These systems are not robust for most real-world applications. In contrast, the system presented here achieves robust performance by using reinforcement learning to induce a mapping from input images to corresponding segmentation parameters... View full abstract»

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  • Task-oriented generation of visual sensing strategies in assembly tasks

    Publication Year: 1998 , Page(s): 126 - 138
    Cited by:  Papers (18)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1988 KB)  

    This paper describes a method of systematically generating visual sensing strategies based on knowledge of the assembly task to be performed. Since visual sensing is usually performed with limited resources, visual sensing strategies should be planned so that only necessary information is obtained efficiently. The generation of the appropriate visual sensing strategy entails knowing what informati... View full abstract»

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  • Robust adaptive segmentation of range images

    Publication Year: 1998 , Page(s): 200 - 205
    Cited by:  Papers (46)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (356 KB)  

    We propose a novel image segmentation technique using the robust, adaptive least kth order squares (ALKS) estimator which minimizes the kth order statistics of the squares of residuals. The optimal value of k is determined from the data, and the procedure detects the homogeneous surface patch representing the relative majority of the pixels. The ALKS shows a better tolerance to structured outliers... View full abstract»

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  • An unbiased detector of curvilinear structures

    Publication Year: 1998 , Page(s): 113 - 125
    Cited by:  Papers (211)  |  Patents (17)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (2032 KB)  

    The extraction of curvilinear structures is an important low-level operation in computer vision that has many applications. Most existing operators use a simple model for the line that is to be extracted, i.e., they do not take into account the surroundings of a line. This leads to the undesired consequence that the line will be extracted in the wrong position whenever a line with different latera... View full abstract»

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  • Segmentation and factorization-based motion and structure estimation for long image sequences

    Publication Year: 1998 , Page(s): 206 - 211
    Cited by:  Papers (8)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1412 KB)  

    This paper presents a computer algorithm which, given a dense temporal sequence of intensity images of multiple moving objects, can separate the images into regions showing distinct objects and, for those objects which are rotating, calculate the three-dimensional structure and motion View full abstract»

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  • A generic grouping algorithm and its quantitative analysis

    Publication Year: 1998 , Page(s): 168 - 185
    Cited by:  Papers (41)  |  Patents (1)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1716 KB)  

    This paper presents a generic method for perceptual grouping and an analysis of its expected grouping quality. The grouping method is fairly general: It may be used for the grouping of various types of data features, and to incorporate different grouping cues operating over feature sets of different sizes. The proposed method is divided into two parts: constructing a graph representation of the av... View full abstract»

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  • Grouping-based nonadditive verification

    Publication Year: 1998 , Page(s): 186 - 192
    Cited by:  Papers (6)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1156 KB)  

    Verification is the final decision stage in many object recognition processes. It is carried out by evaluating a score for every hypothesis and choosing the hypotheses associated with the highest score. This paper suggests a grouping-based verification paradigm, relying on the observation that a group of data features belonging to a hypothesized object instance should be a “good group”... View full abstract»

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  • Extracting 3D vortices in turbulent fluid flow

    Publication Year: 1998 , Page(s): 193 - 199
    Cited by:  Papers (14)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (656 KB)  

    This paper presents a computational framework to extract salient patterns, called vortex structures, from 3D turbulent fluid flows. These structures can be characterized as regions of dominating rotational motion in the velocity fields and intensity concentrations in the corresponding vorticity fields. A pointwise linear representation is employed to approximate the kinematics of the flow field, a... View full abstract»

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  • Analysis of photometric properties of occluding edges by the reversed projection blurring model

    Publication Year: 1998 , Page(s): 155 - 167
    Cited by:  Papers (25)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (516 KB)  

    This paper analyzes photometric properties of occluding edges and proves that an object surface behind a nearer object is partially observable beyond the occluding edges. We first discuss a limitation of the image blurring model using the convolution, and then present an optical flux based blurring model named the reversed projection blurring (RPB) model. Unlike the multicomponent blurring model p... View full abstract»

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  • Linear programming fitting of implicit polynomials

    Publication Year: 1998 , Page(s): 212 - 217
    Cited by:  Papers (7)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (264 KB)  

    A new implicit polynomial (IP) fitting method is presented. It provides a different way of viewing the IP fitting problem from those of the nonlinear optimization approaches. It requires less computation, and can be done automatically or interactively. Linear programming is used to do the fitting. The approach can incorporate a variety of distance measures and global geometric constraints View full abstract»

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  • Decomposition of arbitrarily shaped binary morphological structuring elements using genetic algorithms

    Publication Year: 1998 , Page(s): 217 - 224
    Cited by:  Papers (15)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (240 KB)  

    A number of different algorithms have been described in the literature for the decomposition of both convex binary morphological structuring elements and a specific subset of nonconvex ones. Nevertheless, up to now no deterministic solutions have been found to the problem of decomposing arbitrarily shaped structuring elements. This work presents a new stochastic approach based on genetic algorithm... 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