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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 11 • Date Nov 1994

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Displaying Results 1 - 11 of 11
  • Using symbolic computation to find algebraic invariants

    Page(s): 1143 - 1149
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    Implicit polynomials have proved themselves as having excellent representation power for complicated objects, and there is growing use of them in computer vision, graphics, and CAD. A must for every system that tries to recognize objects based on their representation by implicit polynomials are invariants, which are quantities assigned to polynomials that do not change under coordinate transformations. In the recognition system developed at the Laboratory for Engineering Man-Machine Studies in Brown University (LEMS), it became necessary to use invariants which are explicit and simple functions of the polynomial coefficients. A method to find such invariants is described and the new invariants presented. This work addresses only the problem of finding the invariants; their stability is studied in another paper View full abstract»

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  • On Poisson solvers and semi-direct methods for computing area based optical flow

    Page(s): 1133 - 1138
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    Simchony, Chellappa, and Shao (1990) proposed a semi-direct method for computing area based optical flow. Their method is based on the iterative application of a direct Poisson solver. This method is restricted to Dirichlet boundary conditions, i.e., it is applicable only when velocity vectors at the boundary of the domain are known a priori. The authors show, both experimentally and through analysis, that the semi-direct method converges only for very large smoothness. At such levels of smoothness, the solution is obtained merely by filling in the known boundary values; the data from the image is almost totally ignored. Next, the authors consider the Concus and Golub method (1973), another semi-direct method, for computing optical flow. This method always converges, but the convergence is too slow to be of any practical value. The authors conclude that semi-direct methods are not suited for the computation of area based optical flow View full abstract»

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  • Computation of surface geometry and segmentation using covariance techniques

    Page(s): 1114 - 1116
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    In this correspondence, the application of covariance techniques to surface representation of 3-D objects is discussed and such ways of computing surface geometry are compared with traditional methods using differential geometry. It is shown how the covariance method provides surface descriptors that are invariant to rigid motions without explicitly using surface parameterizations or derivatives. Analogous covariance operators for both the Gauss and Weingarten maps are defined and a range image segmentation technique is presented that labels pixels as jump or crease discontinuities or planar, parabolic or curved region types View full abstract»

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  • Motion estimation via cluster matching

    Page(s): 1128 - 1132
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    A new method for estimating displacements in computer imagery through cluster matching is presented. Without reliance on any object model, the algorithm clusters two successive frames of an image sequence based on position and intensity. After clustering, displacement estimates are obtained by matching the cluster centers between the two frames using cluster features such as position, intensity, shape and average gray-scale difference. The performance of the algorithm was compared to that of a gradient method and a block matching method. The cluster matching approach showed the best performance over a broad range of motion, illumination change and object deformation View full abstract»

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  • Depth and image recovery using a MRF model

    Page(s): 1117 - 1122
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    This paper deals with the problem of depth recovery and image restoration from sparse and noisy image data. The image is modeled as a Markov random field and a new energy function is developed to effectively detect discontinuities in highly sparse and noisy images. The model provides an alternative to the use of a line process. Interpolation over missing data sites is first done using local characteristics to obtain initial estimates and then simulated annealing is used to compute the maximum a posteriori (MAP) estimate. A threshold on energy reduction per iteration is used to speed up simulated annealing by avoiding computation that contributes little to the energy minimization. Moreover, a minor modification of the posterior energy function gives improved results for random as well as structured sparsing problems. Results of simulations carried out on real range and intensity images along with details of the simulations are presented View full abstract»

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  • A game-theoretic approach to integration of modules

    Page(s): 1074 - 1086
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    This paper offers a new approach to integration of modules in an intelligent sensor system. Such a system requires that a set of modules-each doing a smaller portion of the overall task-be integrated within a unifying framework. From the perspective of computational systems, this problem holds a considerable interest because it is characterized by a set of coexisting mathematical objectives that need to be optimized simultaneously. In this sense, the design considerations necessitate the introduction of problem solving with multiple objectives. This paper explores these issues in the instance when each module is associated with a mathematical objective that is a function of the outputs of other modules. The integration problem is formulated and what is required of a good solution is presented. This examination interprets the decentralized mediation of conflicting subgoals as promoting a N-player game amongst the modules to be integrated and proposes a game-theoretic integration framework. We model the interaction among the modules as a noncooperative game and argue that this strategy leads to a framework in which the solutions correspond to a compromise decision. The application of this framework in image analysis motivates the hope that a framework such as game-theoretic integration will facilitate the development of general design principles for “modular” systems View full abstract»

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  • The morphological structure of images: the differential equations of morphological scale-space

    Page(s): 1101 - 1113
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    We introduce a class of nonlinear differential equations that are solved using morphological operations. The erosion and dilation act as morphological propagators propagating the initial condition into the “scale-space”, much like the Gaussian convolution is the propagator for the linear diffusion equation. The analysis starts in the set domain, resulting in the description of erosions and dilations in terms of contour propagation. We show that the structuring elements to be used must have the property that at each point of the contour there is a well-defined and unique normal vector. Then given the normal at a point of the dilated contour we can find the corresponding point (point-of-contact) on the original contour. In some situations we can even link the normal of the dilated contour with the normal in the point-of-contact of the original contour. The results of the set domain are then generalized to grey value images. The role of the normal is replaced with the function gradient. The same analysis also holds for the erosion. Using a family of increasingly larger structuring functions we are then able to link infinitesimal changes in grey value with the gradient in the image View full abstract»

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  • Segmenting simply connected moving objects in a static scene

    Page(s): 1138 - 1142
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    A new segmentation algorithm is derived, based on an object-background probability estimate exploiting the experimental fact that the statistics of local image derivatives show a Laplacian distribution. The objects' simple connectedness is included directly into the probability estimate and leads to an iterative optimization approach that can be implemented efficiently. This new approach avoids early thresholding, explicit edge detection, motion analysis, and grouping View full abstract»

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  • On the hierarchical Bayesian approach to image restoration: applications to astronomical images

    Page(s): 1122 - 1128
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    In an image restoration problem one usually has two different kinds of information. In the first stage, one has knowledge about the structural form of the noise and local characteristics of the restoration. These noise and image models normally depend on unknown hyperparameters. The hierarchical Bayesian approach adds a second stage by putting a hyperprior on the hyperparameters, where information about those hyperparameters is included. In this work the author applies the hierarchical Bayesian approach to image restoration problems and compares it with other approaches in handling the estimation of the hyperparameters View full abstract»

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  • SLIDE: subspace-based line detection

    Page(s): 1057 - 1073
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    An analogy is made between each straight line in an image and a planar propagating wavefront impinging on an array of sensors so as to obtain a mathematical model exploited in recent high resolution methods for direction-of-arrival estimation in sensor array processing. The new so-called SLIDE (subspace-based line detection) algorithm then exploits the spatial coherence between the contributions of each line in different rows of the image to enhance and distinguish a signal subspace that is defined by the desired line parameters. SLIDE yields closed-form and high resolution estimates for line parameters, and its computational complexity and storage requirements are far less than those of the standard method of the Hough transform. If unknown a priori, the number of lines is also estimated in the proposed technique. The signal representation employed in this formulation is also generalized to handle grey-scale images as well. The technique has also been generalized to fitting planes in 3-D images. Some practical issues of the proposed technique are given View full abstract»

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  • Geometric reasoning for extraction of manufacturing features in iso-oriented polyhedrons

    Page(s): 1087 - 1100
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    This paper investigates the extraction of machining features from boundary descriptions of iso-oriented (having no inclined faces) polyhedrons. We prove that manufacturing the features proposed by our feature extractor results exactly in the desired part-in this respect, the approach is both sound and complete. Our method uses the adjacency information between faces to derive the features. This keeps the determination of isolated features in a part straightforward. However, interaction of features creates difficulties since the adjacency information between some faces is lost. We derive this lost information by considering faces that when extended intersect other faces to form concave edges. The derived face adjacencies are termed virtual links. Augmenting the virtual links to the cavity graph of the object leads to its feature graph, and subgraph matching of primitive graphs in this graph results in feature hypotheses. A feature hypothesis is considered valid if the volume corresponding to it is not shared with the part in question; therefore, we verify the feature hypotheses by checking the regularized intersection of the feature volume and the part. Thus, feature verification employs a constructive solid geometry approach. We have implemented a prototype of the system in the Smalltalk-80 environment View full abstract»

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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.

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David A. Forsyth
University of Illinois