Stereo computation is just one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous resul...
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A set of local interaction field are suggested to replace the δ error term in usual regularization approaches. these local fields bring some computational and conceptual benefits. A set of local oriented position pin...
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the proceedings contain 92 papers. the special focus in this conference is on pattern Analysis, Object recognition and Tracking. the topics include: Computational complexity reduction in eigenspace approaches;an algor...
ISBN:
(纸本)3540634606
the proceedings contain 92 papers. the special focus in this conference is on pattern Analysis, Object recognition and Tracking. the topics include: Computational complexity reduction in eigenspace approaches;an algorithm for intrinsic dimensionality estimation;fully unsupervised clustering using center-surround receptive fields with applications to color-segmentation;multi-sensor fusion with bayesian inference;a vision-based object recognition system for autonomous mobile systems;real-time pedestrian tracking in natural scenes;non-rigid object recognition using principal component analysis and geometric hashing;object identification with surface signatures;computing projective and permutation invariants of points and lines;point projective and permutation invariants;computing 3D projective invariants from points and lines;extraction of filled-in data from color forms;improvement of vessel segmentation by elastically compensated patient motion in digital subtraction angiography images;three-dimensional quasi-binary image restoration for confocal microscopy and its application to dendritic trees;mosaicing of flattened images from straight homogeneous generalized cylinders;well-posedness of linear shape-from-shading problem;comparing convex shapes using minkowski addition;deformation of discrete object surfaces;non-archimedean normalized fields in texture analysis tasks;the radon transform-based analysis of bidirectional structural textures;textures and structural defects;self-calibration from the absolute conic on the plane at infinity;a badly calibrated camera in ego-motion estimation-propagation of uncertainty;6DOF calibration of a camera with respect to the wrist of a 5-axis machine tool;automated camera calibration and 3D egomotion estimation for augmented reality applications and optimally rotation-equivariant directional derivative kernels.
We approximate Gaussian function with any scale by linear combination of Gaussian functions with dyadic scales so that scale space can be constructed much more efficiently. the approximation error is so small that our...
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In this paper, we propose a novel method for extracting the geometric primitives from geometric data. Specifically, we use tabu search to solve geometric primitive extraction problem. In the best of our knowledge, it ...
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thin network extraction from three dimensional images is a new issue in computervision. It is of major importance in medical vascular imaging for diagnostic, therapy planning and surgery. In this paper, we develop a ...
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3D pose estimation from 2D image data is a fundamental problem in computervision. In this paper, a pose estimation method based on planar-curved features on the surface of an object is presented. this method is linea...
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We approximate Gaussian function with any scale by linear combination of Gaussian functions with dyadic scales so that scale space can be constructed much more efficiently. the approximation error is so small that our...
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ISBN:
(纸本)081867282X
We approximate Gaussian function with any scale by linear combination of Gaussian functions with dyadic scales so that scale space can be constructed much more efficiently. the approximation error is so small that our approach can be used widely in computervision and patternrecognition. Features at any scale can also be found efficiently by tracking from the dyadic scales.
In this paper, we propose a novel method for extracting the geometric primitives from geometric data. Specifically, we use tabu search to solve geometric primitive extraction problem. In the best of our knowledge, it ...
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ISBN:
(纸本)081867282X
In this paper, we propose a novel method for extracting the geometric primitives from geometric data. Specifically, we use tabu search to solve geometric primitive extraction problem. In the best of our knowledge, it is the first attempt that tabu search is used in computervision. Our tabu search (TS) has a number of advantages: (1) TS avoids entrapment in local minima and continues the search to give a near-optimal final solution; (2) TS is very general and conceptually much simpler than either SA or GA; (3) TS is very easy to implement and the entire procedure only occupies a few lines of code; (4) TS is a flexible framework of a variety of strategies originating from artificial intelligence and is therefore open to further improvement.
thin network extraction from three dimensional images is a new issue in computervision. It is of major importance in medical vascular imaging for diagnostic, therapy planning and surgery. In this paper, we develop a ...
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thin network extraction from three dimensional images is a new issue in computervision. It is of major importance in medical vascular imaging for diagnostic, therapy planning and surgery. In this paper, we develop a framework for automatic thin network extraction from the volumic image. the approach consists in treating the 3D image as a hyper-surface of IR/sup 4/. It is shown that the crest points of this hyper-surface correspond to the center line of the thin network in the image. Using a simple mathematical model, we establish the relationship between the computed principal curvatures of the hyper-surface and the geometry of the network. Promising results are shown on synthetic and real vascular images.
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