In this paper, we present an AR framework that allows natural hand and tangible AR interaction for physically-based interaction and environment awareness to support face-to-face collaboration using Microsoft Kinect. O...
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Similar to ballistic tests in which we match a gun to its bullets, we can identify a given digital camera that acquired an image under investigation. In this paper, we discuss a method for identifying whether or not a...
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Similar to ballistic tests in which we match a gun to its bullets, we can identify a given digital camera that acquired an image under investigation. In this paper, we discuss a method for identifying whether or not an image was captured by a specific digital camera. The method relies on noise residual features related to the images under investigation. Our approach considers an ``open set" recognition scenario, under which we can not rely on the assumption of full access to all of the potential source cameras. This is the only scenario investigators are faced with in the real world. In this case, we model the decision space to take advantage of a few known cameras and carve the decision boundaries to decrease false matches increasing the reliability of image source attribution as an aid for digital forensics in the court of law. This approach performs favorably vs. the state-of-the-art.
This paper proposes a new methodology for micro pattern analysis in digital images based on fuzzy numbers. A micro-pattern is the structure of the gray-level pixels within a neighborhood and can describe the spatial c...
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This paper proposes a new methodology for micro pattern analysis in digital images based on fuzzy numbers. A micro-pattern is the structure of the gray-level pixels within a neighborhood and can describe the spatial context of the image, such as edge, line, spot, blob, corner, texture, and more complex patterns. By treating a pixel neighborhood as a fuzzy set and each pixel gray-level as a fuzzy number, we can evaluate the membership degree of the central pixel to the others. We have called this method the Local Fuzzy Pattern (LFP). Using a sigmoid membership function, we proved that the proposed methodology surpasses the Hit-rate of the Local Binary Pattern (LBP), for texture classification. The LFP proved to be robust to image rotation. Moreover, our proposed formulation for the LFP is a generalization of previously published techniques, such as Texture Unit, LBP, FUNED, and Census Transform.
Ambient occlusion is a low-cost technique to simulate indirect ambient illumination in a realistic way. The goal is to estimate the amount of incident ambient light at each visible point. In this paper, we propose a n...
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Ambient occlusion is a low-cost technique to simulate indirect ambient illumination in a realistic way. The goal is to estimate the amount of incident ambient light at each visible point. In this paper, we propose a novel ambient occlusion method that produces good quality results in real time. Using an efficient voxelization algorithm, we create a volumetric description of the scene geometry in a regular grid. During scene rendering, the hemisphere around each visible point is sampled by a set of cones, each one representing a package of rays. The volume of each cone is sampled by a series of spheres. The obstructed volumes of the spheres are used to estimate the amount of rays that are blocked by the scene geometry. The final ambient occlusion at each visible point is computed by considering all cones in the hemisphere. This approach has shown to be quite adequate: the intersection of each sphere with the voxelized scene is performed in a very efficient manner, and good quality results are achieved with a small number of cones. Computational experiments demonstrate the efficiency and effectiveness of our proposal.
Cloud computing is rapidly becoming one of the most prevailing computing platforms. At the same time, the Web browser has become an application platform. Mobile+Cloud, the combination of mobile devices and cloud-based...
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Cloud computing is rapidly becoming one of the most prevailing computing platforms. At the same time, the Web browser has become an application platform. Mobile+Cloud, the combination of mobile devices and cloud-based computing is changing how users produce, consume, and use computing resources. With the introduction and penetration of HTML5, and, in particular, its visual capabilities in the form of the Canvas element, the implementation of high-quality browser-based graphics has become a reality. Indeed, WebGL offers capabilities comparable to the traditional (desktop) OpenGL utilizing in browser computing resources. It is now feasible to have high performance graphics and visualization "in your palm, " utilizing a mobile device's browser as the graphics platform as well as the front end interface and the display. In the near future, graphics'"heavy lifting" on a cloud-based platform, coupled with a mobile client will afford high-performance graphics for most users most of the time. We argue that this will become the most common platform for computergraphics and visualization in the not too-distant future. We further argue that such platforms will democratize the use of advanced graphics and visualization and will revolutionize analysis and display of the growing amount of data we all face every day. The goals of this survey are to make the reader familiar with the underlying technologies that make this possible, including(but not limited to) cloud-based computing, mobile computing, their combination, HTML5 and the Canvas element, the Web Gland other graphics libraries, and general Web-based graphics and visualization.
Although several methods for pedestrian tracking can be found in the literature, robustly tracking a person in unconstrained environments is an open and active research problem. In this paper, we propose a method that...
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Although several methods for pedestrian tracking can be found in the literature, robustly tracking a person in unconstrained environments is an open and active research problem. In this paper, we propose a method that represents each pedestrian as a set of multiple fragments, aiming robustness with respect to occlusions. These patches are tracked individually and their translation vectors are combined robustly in the world coordinate frame using Weighted Vector Median Filters (WVMF). Additionally, the algorithm uses the camera parameters to both estimate the person scale in a straightforward manner and to limit the search region used to track each fragment. Experiments carried out using two publicly available datasets (PETS and Town Centre) are presented, and they indicate that the proposed method is robust to partial occlusions and large scale changes. According to our experiments, the proposed approach outperforms, regarding the quality of localization, some of the methods in the current state of the art.
Most image colorization techniques assign colors to grayscale images by embedding image pixels into a high dimensional feature space and applying a color pattern to each cluster of high-dimensional data. A main drawba...
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Most image colorization techniques assign colors to grayscale images by embedding image pixels into a high dimensional feature space and applying a color pattern to each cluster of high-dimensional data. A main drawback of such an approach is that, depending on texture patterns and image complexity, clusters of similar pixels can hardly be defined automatically, rendering existing methods prone to fail. In this work we present a novel approach to colorize grayscale images that allows for user intervention. Our methodology makes use of multidimensional projection to map high-dimensional data to a visual space. User can manipulate projected data in the visual space so as to further improve clusters and thus the colorization result. Different from other methods, our interactive tool is ease of use while still being flexible enough to enable local color modification. We show the effectiveness of our approach through a set of examples and comparisons against existing colorization methods.
The quantum noise, intrinsic to the acquisition of X-ray images, becomes more significant during the processes related to fluoroscopy due to its low signal to noise ratio. In this condition, and if there is presence o...
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The quantum noise, intrinsic to the acquisition of X-ray images, becomes more significant during the processes related to fluoroscopy due to its low signal to noise ratio. In this condition, and if there is presence of motion in the image sequence, the use of temporal filtering is restricted, because it will lead to the generation of traces in the resulting filtered images. This artifact can be minimized using purely spatial filtering on regions where motion has been detected. The combination of temporal filtering / spatial filtering results in the hybrid filtering, which is driven by a binary mask of motion detection and it is obtained from the analysis and classification of pixels, based on statistical properties of the image. In this sense, this article aims at contributing to the methods of motion detection, presenting new analyzes in the sensibility of a detection algorithm and tests with real images of X-ray examinations. Preliminary results indicate that the filtering process can be improved with the proper choice of parameters of the motion detection mask for different types of medical X-ray procedures, which differ fundamentally by the amount of relative movement among consecutive frames and the contrast among gray intensities in an image sequence, in relation to the static background.
Sufficient image quality is a necessary prerequisite for reliable automatic detection systems in several healthcare environments. Specifically for Diabetic Retinopathy (DR) detection, poor quality fund us makes more d...
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Sufficient image quality is a necessary prerequisite for reliable automatic detection systems in several healthcare environments. Specifically for Diabetic Retinopathy (DR) detection, poor quality fund us makes more difficult the analysis of discontinuities that characterize lesions, as well as to generate evidence that can incorrectly diagnose the presence of anomalies. Several methods have been applied for classification of image quality and recently, have shown satisfactory results. However, most of the authors have focused only on the visibility of blood vessels through detection of blurring. Furthermore, these studies frequently only used fund us images from specific cameras which are not validated on datasets obtained from different retinographers. In this paper, we propose an approach to verify essential requirements of retinal image quality for DR screening: field definition and blur detection. The methods were developed and validated on two large, representative datasets collected by different cameras. The first dataset comprises 5,776 images and the second, 920 images. For field definition, the method yields a performance close to optimal with an area under the Receiver Operating Characteristic curve (ROC) of 96.0%. For blur detection, the method achieves an area under the ROC curve of 95.5%.
The aim in this paper is to explore whether the Fisher-Rao metric can be used to characterise the shape changes due to gender difference. We work using a 2.5D representation based on facial surface normals (or facial ...
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The aim in this paper is to explore whether the Fisher-Rao metric can be used to characterise the shape changes due to gender difference. We work using a 2.5D representation based on facial surface normals (or facial needle-maps) for gender classification. The needle-map is a shape representation which can be acquired from 2D intensity images using shape-from-shading (SFS). Using the von-Mises Fisher distribution, we compute the elements of the Fisher information matrix, and use this to compute geodesic distance between fields of surface normals to construct a shape-space. We embed the fields of facial surface normals into a low dimensional pattern space using a number of alternative methods including multidimensional scaling, heat kernel embedding and commute time embedding. We present results on clustering the embedded faces using the Max Planck and EAR database.
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