In this research, we propose a new iterative shape from texture (SFT) algorithm which extracts accurate surface depth information of a curved object covered with fairly homogeneous texture directly. The shape informat...
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In this research, we propose a new iterative shape from texture (SFT) algorithm which extracts accurate surface depth information of a curved object covered with fairly homogeneous texture directly. The shape information can be inferred from the rate of texture distortion depicted in an image, and therefore the modeling of the projection and surface geometry as well as the estimation of local texture variation are crucial in obtaining accurate surface shape of an object. By introducing semi-perspective projection camera model and a parametric surface model, we establish a new SFT problem formulation called the textural irradiance equation which relates the local texture density called textural intensity to finite surface parameters. Moreover, by adopting an adaptive multiscale filtering scheme for local texture density estimation, in which the scale or frequency band of a local edge filter is chosen adaptively according to the local shape information, we greatly enhance the accuracy of the estimation of the projected local texture densities, and the final reconstructed shape. We demonstrate the performance of the proposed algorithm by the test with several synthetic and real texture images.
Many classical imageprocessing.tasks can be realized as evaluations of a boolean function over subsets of an image. For instance, the simplicity test used in 3D thinning requires examining the 26 neighbors of each vo...
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ISBN:
(纸本)0780342364
Many classical imageprocessing.tasks can be realized as evaluations of a boolean function over subsets of an image. For instance, the simplicity test used in 3D thinning requires examining the 26 neighbors of each voxel and computing a single boolean function of these inputs. In this article, we show how Binary Decision Diagrams can be used to produce automatically very efficient and compact code for such functions. The total number of operations performed by a generated function is at most one test and one branching for each input value (e.g., in the case of 3D thinning, 26 tests and branchings). At each stage, the function is guaranteed to examine only the pertinent input data, i.e., the values which affect the result. As an example, we consider the 30 simplicity test in digital topology, and thinning processes. We produce functions much faster than our previously optimized implementations [17, 4], and than any other implementation we know of In the case of 3D simplicity test, on average, at each voxel only 8.7 neighboring voxel values are examined.
In this paper, we discuss an appearance matching technique for the interpretation of color scenes containing occluded objects. Dealing with occlusions is very difficult, and we have explored the use of an iterative, c...
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ISBN:
(纸本)0818678224;0780342364
In this paper, we discuss an appearance matching technique for the interpretation of color scenes containing occluded objects. Dealing with occlusions is very difficult, and we have explored the use of an iterative, coarse-to-fine correlation-based method that uses hypothesized occlusion events to modify the scene-to-template similarity measure at run-time. Specifically, a binary mask is used to adaptively exclude regions of the template image from the correlation computation. At each iteration, these masks are adjusted based on higher resolution scene data and the occluding interactions between multiple object hypotheses. We present results which demonstrate the technique is reasonably robust over a large database of color test scenes containing objects at a variety of scales, and tolerates minor object rotations and global illumination variations.
This paper proposes a novel approach to extract meaningful content information from video by collaborative integration of image understanding and natural language processing. As an actual example, we developed a syste...
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This paper proposes a novel approach to extract meaningful content information from video by collaborative integration of image understanding and natural language processing. As an actual example, we developed a system that associates faces and names in videos, called Name-It, which is given news videos as a knowledge source, then automatically extracts face and name association as content information. The system can infer the name of a given unknown face image, or guess faces which are likely to have the name given to the system. This paper explains the method with several successful matching results which reveal effectiveness in integrating heterogeneous techniques as well as the importance of real content information extraction from video, especially face-name association.
We define a new image feature called the color correlogram and use it for image indexing and comparison. This feature distills the spatial correlation of colors, and is both effective and inexpensive for content-based...
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We define a new image feature called the color correlogram and use it for image indexing and comparison. This feature distills the spatial correlation of colors, and is both effective and inexpensive for content-based image retrieval. The correlogram robustly tolerates large changes in appearance and shape caused by changes in viewing positions, camera zooms, etc. Experimental evidence suggests that this new feature outperforms not only the traditional color histogram method but also the recently proposed histogram refinement methods for image indexing/retrieval.
A model for computing image flow in image sequences containing a very wide range of instantaneous flows is proposed. This model integrates the spatio-temporal image derivatives from multiple temporal scales to provide...
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A model for computing image flow in image sequences containing a very wide range of instantaneous flows is proposed. This model integrates the spatio-temporal image derivatives from multiple temporal scales to provide both reliable and accurate instantaneous flow estimates. The integration employs robust regression and automatic scale weighting in a generalized brightness constancy framework. In addition to instantaneous flow estimation the model supports recovery of dense estimates of image acceleration and can be readily combined with parameterized flow and acceleration models. A demonstration of performance on image sequences of typical human actions taken with a high frame-rate camera, is given.
Snakes, or active contours, are used extensively in computer vision and imageprocessing.applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to concave ...
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Snakes, or active contours, are used extensively in computer vision and imageprocessing.applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to concave boundaries, however, have limited their utility. This paper develops a new external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. The resultant field has a large capture range and forces active contours into concave regions. Examples on simulated images and one real image are presented.
We present in this paper a novel calibration method that uses cross ratio to compute world points falling onto any given light stripe plane of a structured light system. We show that, by using 4 known non-coplanar set...
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We present in this paper a novel calibration method that uses cross ratio to compute world points falling onto any given light stripe plane of a structured light system. We show that, by using 4 known non-coplanar sets of 3 collinear world points, the direct 4×3 image to-world transformation matrix for each light stripe plane can also be recovered from plane-to-plane homography. Preliminary experiments conducted with a calibration target and a mannequin suggest that this novel calibration method is robust and is applicable to many shape measurement tasks.
We present a computational, group-theoretic approach to steerable functions. The approach is group-theoretic in that the treatment involves continuous transformation groups for which elementary Lie group theory may be...
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We present a computational, group-theoretic approach to steerable functions. The approach is group-theoretic in that the treatment involves continuous transformation groups for which elementary Lie group theory may be applied. The approach is computational in that the theory is constructive and leads directly to a procedural implementation. For functions that are steerable with n finite number of basis functions under a k-parameter group, the procedure is efficient and is guaranteed to return the minimum number of basis functions. If the function is not steerable, a numerical implementation of the procedure could also be used to compute basis functions that approximately steer the function over a range of transformation parameters. Examples of both applications are demonstrated.
A technique is introduced for extracting and reconstructing a wide class of building types from a registered range image and optical image. An attentional focus stage, followed by model indexing, allows topdown robust...
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A technique is introduced for extracting and reconstructing a wide class of building types from a registered range image and optical image. An attentional focus stage, followed by model indexing, allows topdown robust surface fitting to reconstruct the 3D nature of the buildings in the data. Because of the effectiveness of model selection, top-down processing.of noisy range data still succeeds and the algorithm is capable of detecting and reconstructing several different building roof classes, including flat single level, flat multi-leveled, peaked, and curved rooftops. The algorithm is applicable to range data that may have been collected from several different range sensor types. We demonstrate reconstructions of different buildings classes in the presence of large amounts of noise. Our results underline the usefulness of range data when processed in the context of a focus-of-attention area derived from the monocular optical image.
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