We present an efficient technique for modeling and rendering complex surface details defined at multiple scales. Conceptually, meta-relief texture mapping can be described as recursively mapping finer relief-texture l...
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We present an efficient technique for modeling and rendering complex surface details defined at multiple scales. Conceptually, meta-relief texture mapping can be described as recursively mapping finer relief-texture layers on top of coarser ones. Such a factorization has several desirable properties. For instance, it provides a way of simulating highly-complex surface details as a combination of simpler and inexpensive image-based representations. This greatly simplifies the modeling of surface details, enhancing the artists' expressive power. We also introduce a dynamic texture-space ambient-occlusion technique for relief mapping, which greatly improves the quality of relief renderings. We demonstrate the effectiveness of these techniques by creating and rendering a number of meta-relief textures with complex surface details which would have been hard to model directly.
image compositing aims to combine elements from multiple images producing natural-looking results. The Poisson image editing framework can generate seamless compositions, but tends to introduce color changes in the in...
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image compositing aims to combine elements from multiple images producing natural-looking results. The Poisson image editing framework can generate seamless compositions, but tends to introduce color changes in the inserted objects, which may generate unrealistic and unpleasing results. We present an efficient approach for controlling the amount of color preservation in the inserted objects, while ensuring a seamless transition between the foreground and background elements. Our technique modulates a Laplacian membrane according to some automatically computed parameter, which results in more naturally-looking compositions.
The fuzzy co-clustering algorithms are used to solve the problem clustering of large data, multi-dimension, multifeature. When the dimension and size of data increases, the size of the membership function matrix incre...
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graphics applications have generated visual effects increasingly realistic and for such purpose, reflection effects are essential. To render realistic images, the reflectance of surfaces must be simulated accurately. ...
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ISBN:
(纸本)9781467388443
graphics applications have generated visual effects increasingly realistic and for such purpose, reflection effects are essential. To render realistic images, the reflectance of surfaces must be simulated accurately. In this context, it is common to use ray tracing, since it represents with great fidelity the behavior of light. However, ray tracing is still a very costly algorithm, so far indicated only in offline rendering scenarios. This paper presents a new hybrid solution for generating realistic rendering of objects in 3D walkthroughs. Moreover, the results show that our algorithm has a competitive performance, especially in generating high quality fast reflections, when comparing with those generated with a fully implemented ray tracing algorithm.
In this paper we studied the impact that the directedness of touch interaction has on a path following task performed on a stereoscopic display. The richness of direct touch interaction comes with the potential risk o...
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Clustering techniques have been widely used in areas that handle massive amounts of data, such as statistics, information retrieval, data mining and image analysis. This work presents a novel image clustering method c...
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Clustering techniques have been widely used in areas that handle massive amounts of data, such as statistics, information retrieval, data mining and image analysis. This work presents a novel image clustering method called Partial Least Square image Clustering (PLSIC), which employs a one against-all Partial Least Squares classifier to find image clusters with low redundancy (each cluster represents different visual concept) and high purity (two visual concepts should not be in the same cluster). The main goal of the proposed approach is to find groups of images in an arbitrary set of unlabeled images to convey well defined visual concepts. As a case study, we evaluate the PLSIC to the video summarization problem by means of experiments with 50 videos from various genres of the Open Video Project, comparing summaries generated by the PLSIC with other video summarization approaches found in the literature. A experimental evaluation demonstrates that the proposed method can produce very satisfactory results.
In this paper we present new constraints for calibration of underwater stereo-camera-systems and 3D-reconstruction. These constraints are both intuitive and simple to realize. We show that additionally needed refracti...
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In this paper we present new constraints for calibration of underwater stereo-camera-systems and 3D-reconstruction. These constraints are both intuitive and simple to realize. We show that additionally needed refractive parameters in such a system can be calibrated simultaneously. Our constraints partially build upon each other. A subset of them even enables the calibration from stereo-correspondences alone, making known calibration targets unnecessary.
The difficulty to understand the complex behavior of vector fields makes its visual segmentation an area of constant interest in scientific visualization. In this paper, we present a novel interactive segmentation fra...
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The difficulty to understand the complex behavior of vector fields makes its visual segmentation an area of constant interest in scientific visualization. In this paper, we present a novel interactive segmentation framework for discrete vector fields. In our method, the vector field domain is partitioned into multiple regions with same flow patterns. In order to accomplish this task, feature vectors are extracted from streamlines and mapped to a visual space using multidimensional projection. The interactivity with projected data in the visual space improves the results of the segmentation according to user's knowledge. The provided results and comparisons show the flexibility and effectiveness of our framework.
The proceedings contain 81 papers. The special focus in this conference is on Computational Bioimaging, computergraphics, Motion and Tracking. The topics include: Graph-based visualization of neuronal connectivity us...
ISBN:
(纸本)9783319278568
The proceedings contain 81 papers. The special focus in this conference is on Computational Bioimaging, computergraphics, Motion and Tracking. The topics include: Graph-based visualization of neuronal connectivity using matrix block partitioning and edge bundling;fuzzy skeletonization improves the performance of characterizing trabecular bone micro-architecture;thermal infrared imageprocessing to assess heat generated by magnetic nanoparticles for hyperthermia applications;visualization techniques for the developing chicken heart;an interactive rendering framework for health care support;image annotation incorporating low-rankness, tag and visual correlation and inhomogeneous errors;extracting surface geometry from particle-based fracture simulations;interactive procedural building generation using kaleidoscopic iterated function systems;motion priors estimation for robust matching initialization in automotive applications;multi-target tracking using sample-based data association for mixed images;a hierarchical frame-by-frame association method based on graph matching for multi-object tracking;experimental evaluation of rigid registration using phase correlation under illumination changes;multi-modal computer vision for the detection of multi-scale crowd physical motions and behavior in confined spaces;hmm based evaluation of physical therapy movements using kinect tracking;segmentation of partially overlapping nanoparticles using concave points;an efficient non-parametric background modeling technique with CUDA heterogeneous parallel architecture;finding the n-cuts of watershed partitions for image segmentation;estimating the dominant orientation of an object using image segmentation and principal component analysis and unscented transformation and matrix rank optimization for moving objects detection in aerial imagery.
In this paper, we present an unsupervised approach for estimating the effectiveness of image retrieval results obtained for a given query. The proposed approach does not require any training procedure and the computat...
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In this paper, we present an unsupervised approach for estimating the effectiveness of image retrieval results obtained for a given query. The proposed approach does not require any training procedure and the computational efforts needed are very low, since only the top-k results are analyzed. In addition, we also discuss the use of the unsupervised measures in two novel rank aggregation methods, which assign weights to ranked lists according to their effectiveness estimation. An experimental evaluation was conducted considering different datasets and various image descriptors. Experimental results demonstrate the capacity of the proposed measures in correctly estimating the effectiveness of different queries in an unsupervised manner. The linear correlation between the proposed and widely used effectiveness evaluation measures achieves scores up to 0.86 for some descriptors.
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