A novel scene reconstruction technique is presented, different from previous approaches in its ability to cope with large changes in visibility and its modeling of intrinsic scene color and texture information. The me...
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A novel scene reconstruction technique is presented, different from previous approaches in its ability to cope with large changes in visibility and its modeling of intrinsic scene color and texture information. The method avoids image correspondence problems by working in a discretized scene space whose voxels are traversed in a fixed visibility ordering. This strategy takes full account of occlusions and allows the input cameras to be far apart and widely distributed about the environment. The algorithm identifies a special set of invariant voxels which together form a spatial and photometric reconstruction of the scene, fully consistent with the input images. The approach is evaluated with images from both inward- and outward-facing cameras.
This paper will review the design of a working system that visually recognizes hand gestures for the control of a window based user interface. After an overview of the system, it will explore one aspect of gestural in...
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This paper will review the design of a working system that visually recognizes hand gestures for the control of a window based user interface. After an overview of the system, it will explore one aspect of gestural interaction in depth, hand tracking, and what is needed for the user to be able to interact comfortably with on-screen objects. We describe how the location of the hand is mapped to a location on the screen, and how it is both necessary and possible to smooth the camera input using a non-linear physical model of the cursor. The performance of the system is examined, especially with respect to abject selection. We show how a standard HCI model of object selection (Fitts' Law) can be extended to model the selection performance of free-hand pointing.
In this paper, a correlational approach for distinguishing occluding contours from object markings for 3D object modeling is presented. The proposed method is valid under weak perspective projection, does not require ...
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In this paper, a correlational approach for distinguishing occluding contours from object markings for 3D object modeling is presented. The proposed method is valid under weak perspective projection, does not require to search for correspondences between frames, can handle scaling between consecutive images. Thus can estimate the full Euclidean surface structure, and does not require camera calibration or camera motion measurement. Extensive experimental results show that the method is robust to the occlusion of feature points and image noise unlike previous affine-based approaches. Qualitative and quantitative results for the relation between the required minimum viewing angle change for the detection and the surface curvature are also presented.
Texture has long been regarded as spatial distributions of gray-level variation, and texture analysis has generally been confined to the 2-D image domain. Introducing the concept of "3-D world feature", this...
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Texture has long been regarded as spatial distributions of gray-level variation, and texture analysis has generally been confined to the 2-D image domain. Introducing the concept of "3-D world feature", this paper considers texture as a function of 3-D structures and proposes a set of "3-D textural features". The proposed 3-D features appear to have a great potential in terrain classification. Experiments have been carried out to compare the 3-D features with a popular traditional 2-D feature set. The results show that the 3-D features significantly outperform the 2-D features in terms of classification accuracy.
A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3...
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A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3D information from 2D views of the jaw, and a novel technique for 3D data registration using genetic algorithms. The resulting 3D model can be used for diagnosis, treatment planning, and implant purposes. The overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. This system will be flexible, accurate, and will reduce the cost of orthodontic treatments.
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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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 3D simplicity test in digital topology, and thinning processes. We produce functions much faster than our previously optimized implementations 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.
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 top-down robus...
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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 top-down 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.
We present the concept of non-rigid matching based on demons, by reference to Maxwell's demons. We contrast this concept with the more conventional viewpoint of attraction. We show that demons and attractive point...
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ISBN:
(纸本)0818672587
We present the concept of non-rigid matching based on demons, by reference to Maxwell's demons. We contrast this concept with the more conventional viewpoint of attraction. We show that demons and attractive points are clearly distinct for large deformations, but also that they become similar for small displacements, encompassing techniques close to optical flow. We describe a general iterative matching method based on demons, and derive from it three different non-rigid matching algorithms, one using all the image intensities, one using only contours, and one for already segmented images. At last, we present results with synthesized and real deformations, with applications to computer Vision and Medical imageprocessing.
The use of visual representations in which retinal neurons receptive fields are not constant over the visual field is universal in the visual systems of higher vertebrates, and is coming to play an important role in a...
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ISBN:
(纸本)0818672587
The use of visual representations in which retinal neurons receptive fields are not constant over the visual field is universal in the visual systems of higher vertebrates, and is coming to play an important role in active vision applications. The breaking of translation symmetry that is unavoidably associated with nonuniform sampling presents a major algorithmic complication for imageprocessing. In this paper we use a Lie group approach to derive a kernel which provides a quasi-shift (i.e. approximate shift) invariant template matching capability, under normal convolution in the distorted (range) coordinates of the non-uniform mapping. We work out the special case of the log-polar mapping, which is of great interest in vision;in this case, we call the associated linear integral transform the 'exponential chirp transform' (ECT). The method is, however, general for other forms of mapping, or warp, function.
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