In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic a...
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In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic algorithm is applied to realize the final annotation. Experiments with images from the beach vacation domain demonstrate the performance of the proposed approach and illustrate the added value of utilizing contextual information.
Presents a new algorithm for segmentation of noisy or textured images using the expectation-maximization (EM) algorithm for estimating parameters of the probability mass function of the pixel class labels and the maxi...
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Presents a new algorithm for segmentation of noisy or textured images using the expectation-maximization (EM) algorithm for estimating parameters of the probability mass function of the pixel class labels and the maximization of the posterior marginals (MPM) criterion for the segmentation operation. A Markov random field (MRF) model is used for the pixel class labels. The authors present experimental results demonstrating the use of the new algorithm on synthetic images and medical imagery.< >
We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions...
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We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions to guide the sequential search at higher resolutions. As a consequence, the dependence on a priori knowledge of the image edges is greatly reduced. Estimating the sequential search parameters from lower resolution images provides for a more accurate and less costly search of edge paths in the image.
This study addresses a problem that arises in the early stages of visual processing. Low-level visionprocessing tasks generate information describing distances and orientations at sparse locations of visible surfaces...
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This study addresses a problem that arises in the early stages of visual processing. Low-level visionprocessing tasks generate information describing distances and orientations at sparse locations of visible surfaces in a scene. The information from these various low-level tasks need to be combined to form an estimate of the visual surface for all points in the scene. This step is commonly referred to as the surface reconstruction problem. The problem is cast as an ill-posed inverse problem, which must be stabilized using a priori information relative to image and constraint formation. A desirable property of any reconstruction algorithm is invariance with respect to rigid transformations of the surface in three-dimensional space. Two surface reconstruction algorithms that are based on invariant surface characteristics are proposed. These algorithms are studied in detail, and an example is presented to demonstrate their effectiveness. The discrete realization of the algorithms is also briefly discussed.< >
Cardiac function is often evaluated quantitatively using two-dimensional echocardiography to analyze shape attributes, such as the heart wall thickness or the shape change of the heart wall boundaries. A review of pre...
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Cardiac function is often evaluated quantitatively using two-dimensional echocardiography to analyze shape attributes, such as the heart wall thickness or the shape change of the heart wall boundaries. A review of previous work in detecting the heart wall boundaries is presented, along with how this problem can be viewed from a computervision perspective. The principles of echo image sequence analysis and high-level analysis are described. It is suggested that one promising approach is to use multiple-resolution processing by using a large window smoothed image for the initial detection of major edge segments, followed by smaller and smaller windows until a complete boundary is found.< >
In this paper we present new results relative to the "expectation-maximization/maximization of the posterior marginals" (EM/MPM) algorithm for simultaneous parameter estimation and segmentation of textured i...
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In this paper we present new results relative to the "expectation-maximization/maximization of the posterior marginals" (EM/MPM) algorithm for simultaneous parameter estimation and segmentation of textured images. The goal of the EM/MPM algorithm is to minimize the expected value of the number of misclassified pixels. We present new theoretical results in this paper which show that the algorithm can be expected to achieve this goal, to the extent that the EM estimates of the model parameters are close to the true values of the model parameters. We also present new experimental results demonstrating the performance of the algorithm.
Video parsing is a fundamental operation used in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the parsing algorithm is critical if large amounts of v...
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Video parsing is a fundamental operation used in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the parsing algorithm is critical if large amounts of video data are to be processed, particularly in real-time. We present a new algorithm to reconstruct DC coefficient images of a DCT and motion compensation compressed video sequence, e.g. MPEG. The histograms of the DC coefficient images can be used to detect scene changes.
In this paper we describe two error-recovery approaches for MPEG encoded video over ATM networks. The first approach aims at reconstructing each lost pixel by spatial interpolation from the nearest undamaged pixels. T...
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In this paper we describe two error-recovery approaches for MPEG encoded video over ATM networks. The first approach aims at reconstructing each lost pixel by spatial interpolation from the nearest undamaged pixels. The second approach recovers lost macroblocks by minimizing intersample variations within each block and across its boundaries. Moreover, a new technique for packing ATM cells with compressed data is also proposed.
Edge detection is analyzed as a problem in cost minimization. A cost function is formulated that evaluates the quality of edge configurations. A mathematical description of edges is given, and the cost function is ana...
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Edge detection is analyzed as a problem in cost minimization. A cost function is formulated that evaluates the quality of edge configurations. A mathematical description of edges is given, and the cost function is analyzed in terms of the characteristics of the edges in minimum-cost configurations. The cost function is minimized by the simulated annealing method. A novel set of strategies for generating candidate states and a suitable temperature schedule are presented. Sequential and parallel versions of the annealing algorithm are implemented and compared. Experimental results are presented.< >
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