It is often necessary to handle randomness and geometry is computervision, for instance to match and fuse together noisy geometric features such as points, lines or 3D frames, or to estimate a geometric transformatio...
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ISBN:
(纸本)0818672587
It is often necessary to handle randomness and geometry is computervision, for instance to match and fuse together noisy geometric features such as points, lines or 3D frames, or to estimate a geometric transformation from a set of matched features. However, the proper handling of these geometric features is far more difficult than for points, and a number of paradoxes can arise. We analyse in this article three basic problems: (1) what is a uniform random distribution of features, (2) how to define a distance between features, and (3) what is the 'mean feature' of a number of feature measurements, and we propose generic methods to solve them.
We show how shadows can be efficiently generated in differentiable rendering of triangle meshes. Our central observation is that pre-filtered shadow mapping, a technique for approximating shadows based on rendering fr...
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ISBN:
(纸本)9798350301298
We show how shadows can be efficiently generated in differentiable rendering of triangle meshes. Our central observation is that pre-filtered shadow mapping, a technique for approximating shadows based on rendering from the perspective of a light, can be combined with existing differentiable rasterizers to yield differentiable visibility information. We demonstrate at several inverse graphics problems that differentiable shadow maps are orders of magnitude faster than differentiable light transport simulation with similar accuracy - while differentiable rasterization without shadows often fails to converge.
A systematic methodology is presented for automatic selection of scale levels when detecting one-dimensional features, such as edges and ridges. A novel concept of a scale-space edge is introduced and defined as a con...
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ISBN:
(纸本)0818672587
A systematic methodology is presented for automatic selection of scale levels when detecting one-dimensional features, such as edges and ridges. A novel concept of a scale-space edge is introduced and defined as a connected set of points in scale-space. Two specific measures of edge strength are analyzed in detail. It is shown that by expressing these in terms of γ-normalized derivatives, an immediate consequence of this definition is that fine scales are selected for sharp edges, whereas coarse scales are selected for diffuse edge, such that an edge model constitutes a valid abstraction of the intensity profile across the edge.
The trifocal tensor, which describes the relation between projections of points and lines in three views, is a fundamental entity of geometric computervision. In this work, we investigate a new parametrization of the...
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ISBN:
(纸本)9781467369640
The trifocal tensor, which describes the relation between projections of points and lines in three views, is a fundamental entity of geometric computervision. In this work, we investigate a new parametrization of the trifocal tensor for calibrated cameras with non-colinear pinholes obtained from a quotient Riemannian manifold. We incorporate this formulation into state-of-the art methods for optimization on manifolds, and show, through experiments in pose averaging, that it produces a meaningful way to measure distances between trifocal tensors.
Super-Fibonacci spirals are an extension of Fibonacci spirals, enabling fast generation of an arbitrary but fixed number of 3D orientations. The algorithm is simple and fast. A comprehensive evaluation comparing to ot...
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ISBN:
(数字)9781665469463
ISBN:
(纸本)9781665469463
Super-Fibonacci spirals are an extension of Fibonacci spirals, enabling fast generation of an arbitrary but fixed number of 3D orientations. The algorithm is simple and fast. A comprehensive evaluation comparing to other methods shows that the generated sets of orientations have low discrepancy, minimal spurious components in the power spectrum, and almost identical Voronoi volumes. This makes them useful for a variety of applications, in particular Monte Carlo sampling.
Colorization refers to the process of adding color to black & white images or videos. This paper extends the term to handle surfaces in three dimensions. This is important for applications in which the colors of a...
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ISBN:
(纸本)9780769549897
Colorization refers to the process of adding color to black & white images or videos. This paper extends the term to handle surfaces in three dimensions. This is important for applications in which the colors of an object need to be restored and no relevant image exists for texturing it. We focus on surfaces with patterns and propose a novel algorithm for adding colors to these surfaces. The user needs only to scribble a few color strokes on one instance of each pattern, and the system proceeds to automatically colorize the whole surface. For this scheme to work, we address not only the problem of colorization, but also the problem of pattern detection on surfaces.
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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ISBN:
(纸本)0780342364
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 object 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.
We consider a scene, containing many objects moving with constant velocity along straight line paths, seen from three reference viewpoints at three different times. The scene may even consist only of moving objects wi...
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ISBN:
(纸本)0769506623
We consider a scene, containing many objects moving with constant velocity along straight line paths, seen from three reference viewpoints at three different times. The scene may even consist only of moving objects with no static features. We wish to create a new image sequence showing the scene from arbitrary viewing position and arbitrary time. We make use of a newly discovered tool, the "dual Htensor" [1], that connects together three views of a coplanar configuration of (unlabeled) static and moving paints. The newly synthesized images use constant velocity in the world to achive realistic and physically correct images.
The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this pa...
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ISBN:
(纸本)0818672587
The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this paper we present a new approach which successfully solves these problems. The major novelty of our approach lies in the way how the coefficients of the eigenimages are determined. Instead of computing the coefficients by a projection of the data onto the eigenimages, we extract them by a hypothesize-and-test paradigm using subsets of image points. Competing hypotheses are then subject to a selection procedure based on the Minimum Description Length principle. The approach enables us not only to reject outliers and to deal with occlusions but also to simultaneously use multiple classes of eigenimages.
Measuring perceptual saliency of regions in a scene is important for determining regions of interest. Color, texture and shape cues are good low-level features for detecting saliency. While self saliency refers to int...
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ISBN:
(纸本)0769506623
Measuring perceptual saliency of regions in a scene is important for determining regions of interest. Color, texture and shape cues are good low-level features for detecting saliency. While self saliency refers to intrinsic attributes of a region, relative saliency is used to measure how salient a region is relative to its surrounding and, thus, needs to be defined within a spatial context. A few spatial context models are investigated in this study. In particular, we propose an auto-scaled, amorphous neighborhood as the context model to obtain reliable measurements of relative saliency features. Comparison of three contest models has shown that the proposed model is capable of generating predicates more consistent with perceived saliency.
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