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Recent approaches have proposed to empower Internet Service Providers (ISPs) with caching capabilities that can allow them to implement their own cache management strategies and as such have better control over the utilization of their resources. In this demo paper, we present CacheMAsT (Cache Management Analysis and Visualization Tool), a decision support tool to visualize the configuration and performance...
Visual attention is the cognitive process that allows humans to parse a large amount of sensory data by selecting relevant information and filtering out irrelevant stimuli. This papers develops a computational approach for visual attention in robots. We consider a Visual-Inertial Navigation (VIN) problem in which a robot needs to estimate its state using an on-board camera and an inertial sensor....
We propose an active exposure control method to improve the robustness of visual odometry in HDR (high dynamic range) environments. Our method evaluates the proper exposure time by maximizing a robust gradient-based image quality metric. The optimization is achieved by exploiting the photometric response function of the camera. Our exposure control method is evaluated in different real world environments...
Direct visual odometry and Simultaneous Localization and Mapping (SLAM) methods determine camera poses by means of direct image alignment. This optimizes a photometric cost term based on the Lucas-Kanade method. Many recent works use the brightness constancy assumption in the alignment cost formulation and therefore cannot cope with significant illumination changes. Such changes are especially likely...
A variety of end-user devices involving keypoint-based mapping systems are about to hit the market e.g. as part of smartphones, cars, robotic platforms, or virtual and augmented reality applications. Thus, the generated map data requires automated evaluation procedures that do not require experienced personnel or ground truth knowledge of the underlying environment. A particularly important question...
While there is an increased appreciation for integrating haptic feedback with audio-visual content, there is still a lack of understanding of how to quantify the added value of touch for a user's experience (UX) of multimedia content. Here we focus on three main concepts to measure this added value: UX, emotions, and expectations. We present a case study measuring the added value of haptic feedback...
In this paper, we propose a novel no reference (NR) quality assessment metric for stereoscopic images by statistical features. First, we calculate the luminance map through the local normalization, which is further used to extract the statistic luminance features. Second, we predict the disparity map of the stereoscopic image, which is further combined with the corresponding left and right views to...
Code coverage is a metric used to represent how much code is tested when particular test cases are executed. As is code coverage, specification coverage is expected to help us to comprehend how much specification to be implemented is tested. In this study, we propose a visualization process for specification coverage. This process finds traceability links between specifications and test cases using...
This paper addresses the problem of maritime vessel identification by exploiting the state-of-the-art techniques of distance metric learning and deep convolutional neural networks since vessels are the key constituents of marine surveillance. In order to increase the performance of visual vessel identification, we propose a joint learning framework which considers a classification and a distance metric...
Horizon or skyline detection plays a vital role towards mountainous visual geo-localization, however most of the recently proposed visual geo-localization approaches rely on user-in-the-loop skyline detection methods. Detecting such a segmenting boundary fully autonomously would definitely be a step forward for these localization approaches. This paper provides a quantitative comparison of four such...
Light field technology may have a positive impact on several multimedia applications thanks to novel ways to explore the captured scenes, such as changing the parallax (horizontally and vertically) and refocusing the content. These innovative use cases require new considerations that affect the whole processing chain, from content acquisition to visualization, as well as the methodologies for quality...
In this paper, we study the problem of predicting the visual quality of a specific test sample (e.g. a video clip) experienced by a specific user, based on the ratings by other users for the same sample and the same user for other samples. A simple linear model and algorithm is presented, where the characteristics of each test sample are represented by a set of parameters, and the individual preferences...
In this paper we use a Deep Neural Network (DNN) trained on data collected from the visual media-sharing social platform Instagram account of a popular Indian lifestyle magazine to predict the popularity of future posts. This predicted popularity of the post can be used to decide advertising rates and measure performance metrics important for publishing strategy decisions. The DNN primarily uses growth...
Pulmonary emphysema overlaps considerably with chronic obstructive pulmonary disease (COPD), and is traditionally subcategorized into three subtypes: centrilobular emphysema (CLE), panlobular emphysema (PLE) and paraseptal emphysema (PSE). Automated classification methods based on supervised learning are generally based upon the current definition of emphysema subtypes, while unsupervised learning...
The human visual perception is a layered progressive process that brain assimilates visual information gradually, from primary information, structural information to detailed information. Recently, the visual primitives (atoms in the dictionary) extracted by sparse representation have been shown to be highly related to the layered progressive process of human visual perception. In this paper, the...
Enterprises and researchers often have datasets that can be represented as graphs (e.g. social networks). The owner of a large graph may want to scale it down to a similar but smaller version, e.g. for application development. On the other hand, the owner of a small graph may want to scale it up to a similar but larger version, e.g. to test system scalability. GSCALER is a recently developed tool...
Locality sensitive hashing (LSH) and its variants are widely used for approximate kNN (k nearest neighbor) search in high-dimensional space. The success of these techniques largely depends on the ability of preserving kNN information. Unfortunately, LSH only provides a high probability that nearby points in the original space are projected into nearby region in a new space. This potentially makes...
The vast volume of real-time air traffic data, being produced through new digital transmissions of the movement of aircraft throughout the US National Airspace System (NAS), is a rich resource for evaluating the performance of the system. To date, the potential for comprehensively analyzing this data has yet to be tapped, precisely due to a lack of tools that limit fully interactive data visualization...
Whenever a video is being digitized, compressed and transmitted across the network, some degradation might be introduced that could affect the quality of the video received. Thus, it is essential to provide feedback system to the provider which could allow them the freedom to feedback to the system, if the quality of video being transmitted could be improved, in terms of video quality. This is an...
The purpose of research on image quality assessment (IQA) is to find proper methods to measure the quality of images. The subjective evaluation score by HVS is usually used as a standard to be compared with. So, the more similar the measuring process is to HVS, the better the result should be. Motivated by this idea, contourlet transform and singular value decomposition are used in this article to...
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