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.
This paper proposes a novel approach to action recognition from ROB-D cameras, in which depth features and ROB visual features are jointly used. Rich heterogeneous ROB and depth data are effectively compressed and pro...
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ISBN:
(纸本)9781467369640
This paper proposes a novel approach to action recognition from ROB-D cameras, in which depth features and ROB visual features are jointly used. Rich heterogeneous ROB and depth data are effectively compressed and projected to a learned shared space, in order to reduce noise and capture useful information. for recognition. Knowledge from various sources can then be shared with others in the learned space to learn cross-modal features. This guides the discovery of valuable information for recognition. To capture complex spatiotemporal structural relationships in visual and depth features, we represent both ROB and depth data in a matrix form. We formulate the recognition task as a low-rank bilinear model composed of row and column parameter matrices. The rank of the model parameter is minimized to build a low-rank classifier;which is beneficial for improving the generalization power The proposed method is extensively evaluated on two public RGB-D action damsels, and achieves state-of-the-art results. It also shows promising results if ROB or depth data are missing in training or testing procedure,
The alignment of a set of objects by means of transformations plays an important role in computervision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually itera...
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ISBN:
(纸本)9781467369640
The alignment of a set of objects by means of transformations plays an important role in computervision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually iterative methods are used. In practice the iterative methods perform well if the relative transformations between any pair of objects are free of noise. However, if only noisy relative transformations are available (e.g. due to missing data or wrong correspondences) the iterative methods may fail. Based on the observation that the underlying noise-free transformations can be retrieved from the null space of a matrix that can directly be obtained from pairwise alignments, this paper presents a novel method for the synchronisation of pairwise transformations such that they are transitively consistent. Simulations demonstrate that for noisy transformations, a large proportion of missing data and even for wrong correspondence assignments the method delivers encouraging results.
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 propose an approximate shading model for image-based object modeling and insertion. Our approach is a hybrid of 3D rendering and image-based composition. It avoids the difficulties of physically accurate shape esti...
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ISBN:
(纸本)9781467369640
We propose an approximate shading model for image-based object modeling and insertion. Our approach is a hybrid of 3D rendering and image-based composition. It avoids the difficulties of physically accurate shape estimation from a single image, and allows for more flexible image composition than pure image-based methods. The model decomposes the shading field into (a) a rough shape term that can be reshaded, (b) a parametric shading detail that encodes missing features from the first term, and (c) a geometric detail term that captures fine-scale material properties. With this object model, we build an object relighting system that allows an artist to select an object from an image and insert it into a 3D scene. Through simple interactions, the system can adjust illumination on the inserted object so that it appears more naturally in the scene. Our quantitative evaluation and extensive user study suggest our method is a promising alternative to existing methods of object insertion.
Conditional Random Fields (CRFs) are one of the core technologies in computervision, and have been applied to a wide variety of tasks. Conventional CRFs typically define edges between neighboring image pixels, result...
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ISBN:
(纸本)9781467369640
Conditional Random Fields (CRFs) are one of the core technologies in computervision, and have been applied to a wide variety of tasks. Conventional CRFs typically define edges between neighboring image pixels, resulting in a sparse graph over which inference can be performed efficiently. However, these CRFs fail to model more complex priors such as long-range contextual relationships. Fullyconnected CRFs have thus been proposed. While there are efficient approximate inference methods for such CRFs, usually they are sensitive to initialization and make strong assumptions. In this work, we develop an efficient, yet general SDP algorithm for inference on fully-connected CRFs. The core of the proposed algorithm is a tailored quasi-Newton method, which solves a specialized SDP dual problem and takes advantage of the low-rank matrix approximation for fast computation. Experiments demonstrate that our method can be applied to fully-connected CRFs that could not previously be solved, such as those arising in pixel-level image co-segmentation.
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