In this paper, we propose a method to model the Copacabana beach sidewalk pavement, and Portuguese pavements in general. Given a black and white source image, the proposed method outputs the geometry of all individual...
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In this paper, we propose a method to model the Copacabana beach sidewalk pavement, and Portuguese pavements in general. Given a black and white source image, the proposed method outputs the geometry of all individual stones that compose the pavement. Different from previous mosaic techniques, we focus on capturing the particularities of such pavements: the stones (tiles) must completely follow the edges, being mostly represented by irregular quadrilaterals with no particular orientation. A set of experiments demonstrates the effectiveness and stability of our proposal.
This paper describes the use of GPU-specific optimization techniques applied to the problem of simulation of scale free gene regulatory networks based on threshold function on GPU. We made attempts to optimize memory ...
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Visually coherent rendering for augmented reality is concerned with seamlessly blending the virtual world and the real world in real-time. One challenge in achieving this is the correct handling of lighting. We are in...
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ISBN:
(纸本)9781467346627
Visually coherent rendering for augmented reality is concerned with seamlessly blending the virtual world and the real world in real-time. One challenge in achieving this is the correct handling of lighting. We are interested in applying real-world light to virtual objects, and compute the interaction of light between virtual and real. This implies the measurement of the real-world lighting, also known as photometric registration. So far, photometric registration has mainly been done through capturing images with artificial light probes, such as mirror balls or planar markers, or by using high dynamic range cameras with fish-eye lenses. In this paper, we present a novel non-invasive system, using arbitrary scene geometry as a light probe for photometric registration, and a general AR rendering pipeline supporting real-time global illumination techniques. Based on state of the art real-time geometric reconstruction, we show how to robustly extract data for photometric registration to compute a realistic representation of the real-world diffuse lighting. Our approach estimates the light from observations of the reconstructed model and is based on spherical harmonics, enabling plausible illumination such as soft shadows, in a mixed virtual-real rendering pipeline.
Transparency and anti-aliasing are crucial to enhance realism in computer-generated images, which have a high demand for such effects. Transparency is largely used to denote relationships among objects in a scene, and...
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Transparency and anti-aliasing are crucial to enhance realism in computer-generated images, which have a high demand for such effects. Transparency is largely used to denote relationships among objects in a scene, and to render several structures, such as particles and foliage. Anti-aliasing (AA) is also important, since jagged edges can be easily spotted and create disruptive distractions during a scene walkthrough, which are unacceptable in real-time applications. Figure 1 illustrates both effects. In common, they have the fact that they rely on processing discrete samples from a given function, but using the samples for different purposes. In this tutorial we review state-of the-art techniques for transparency and anti-aliasing effects, their initial ideas and subsequent GPU accelerations. We support our presentation with a discussion on their strengths and limitations.
In this paper we present a method to simulate fluids on smooth surfaces of arbitrary topology using a graphicsprocessing unit (GPU). To do this we use the parametrization of Cat mull-Clark subdivision surfaces and ob...
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In this paper we present a method to simulate fluids on smooth surfaces of arbitrary topology using a graphicsprocessing unit (GPU). To do this we use the parametrization of Cat mull-Clark subdivision surfaces and obtain the metric information of the distortion caused by this parametrization, so we can calculate differential operators of functions defined on this surface. Then the Navier-Stokes equations on surfaces are solved in the domain of parametrization of each patch. This process can be done in parallel for each point in the discretization of the surface, so the GPU implementation can heavily increase the velocity of computation.
In this paper, histogram uniformization of digital images by means of the finite field cosine transform (FFCT) is examined. The approach consists in dividing the image into blocks and applying the FFCT, in a recursive...
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In this paper, histogram uniformization of digital images by means of the finite field cosine transform (FFCT) is examined. The approach consists in dividing the image into blocks and applying the FFCT, in a recursive manner, to each block. Simulations of the procedure show that the histogram of the transformed image exhibits a uniform shape and its pixels have low correlation with their neighbors. This result is achieved due to the modular arithmetic used in the application of the FFCT to the image blocks. The suitability of the proposed technique in the context of image encryption is discussed.
We propose a GPU-based algorithm for texture analysis and synthesis of nearly-regular patterns, in our case scanned textiles or similar manufactured surfaces. The method takes advantage of the highly parallel executio...
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ISBN:
(数字)9783642331916
ISBN:
(纸本)9783642331916
We propose a GPU-based algorithm for texture analysis and synthesis of nearly-regular patterns, in our case scanned textiles or similar manufactured surfaces. The method takes advantage of the highly parallel execution on the GPU to generate correlation maps from captured template images. In an analysis step a lattice encoding the periodicity of the texture is computed. This lattice is used to synthesize the smallest texture tile describing the underlying pattern. Compared to other approaches, our method analyzes and synthesizes a valid lattice model without any user interaction. It is robust against small distortions and fast compared to other, more general approaches.
image segmentation is still a challenging issue in pattern recognition. Among the various segmentation approaches are those based on graph partitioning, which present some drawbacks, one being high processing times. W...
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image segmentation is still a challenging issue in pattern recognition. Among the various segmentation approaches are those based on graph partitioning, which present some drawbacks, one being high processing times. With the recent developments on complex networks theory, pattern recognition techniques based on graphs have improved considerably. The identification of cluster of vertices can be considered a process of community identification according to complex networks theory. Since data clustering is related with image segmentation, image segmentation can also be approached via complex networks. However, image segmentation based on complex networks poses a fundamental limitation which is the excessive numbers of nodes in the network. This paper presents a complex network approach for large image segmentation that is both accurate and fast. To that, we incorporate the concept of super pixels, to reduce the number of nodes in the network. We evaluate our method for both synthetic and real images. Results show that our method can outperform other graph-based methods both in accuracy and processing times.
computer Science development plays an important role to understand natural phenomena. Its advance has impacted on studies results from many areas such as Biology and Medicine. Agent-based Models (ABM) are an alternati...
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We present a new formulation to automatically solve jigsaw puzzles considering only the information contained on the image. Our formulation maps the problem of solving a jigsaw puzzle to the maximization of a constrai...
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We present a new formulation to automatically solve jigsaw puzzles considering only the information contained on the image. Our formulation maps the problem of solving a jigsaw puzzle to the maximization of a constrained quadratic function that can be solved by a numerical method. The proposed method is deterministic and it can handle arbitrary rectangular pieces. We tested the validity of the method to solve problems up to 3300 puzzle pieces, and we compared our results to the current state-of-the-art, obtaining superior accuracy.
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