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In sharing information for the research support at university laboratories, not only the research documents including references, seminar documents, research data, and articles but also the context information including the process of the research activities that have been conducted and the relations between the research documents are important. In this study, both research documents and context information...
Most augmented reality applications connect virtual information to anchors, i.e. physical places or objects, by using spatial overlays or proximity. However, for industrial use cases this is not always feasible because specific parts must remain fully visible in order to meet work or security requirements. In these situations virtual information must be displayed at alternative positions while connections...
Mobile devices equipped with cameras, such as smartphones, have become extremely popular in recent years, and have motivated users to capture an increasing number of digital photos in their daily lives. Users often invoke these photos during in-person interactions or conversations with others. In the context of a conversation between two people related to or involving reference to a photo, one of...
This paper presents a new image retargeting method that explores blur information. Given the input image, we compute the blur map and estimate in-focus regions. For retargeting, we first try to crop image boundaries as much as possible (preserving in-focus regions). If cropping is not enough, we use seam carving exploring a novel blur-aware energy function that concentrates the seams in blurred regions...
In this paper, we present a new FFT-based visual tracking algorithm based on a new model for computing prior context distribution via a spectral saliency approach. The tracking problem is formulated under a Bayesian framework where the statistical relationships between the features of the target and its spatio-temporal context are modeled. When building the context model, the prior distribution of...
Existing deep neural networks, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), typically treat volumetric video data as several single images and deal with one frame at one time, thus the relevance to frames can hardly be fully exploited. Besides, depth context plays the unique role in motion scenes for primates, but is seldom used in no depth label situations. In...
The leading advantage of Ultrasound-Guided Regional Anesthesia (UGRA) is the ability to visualize the anatomical structure of interest. The nerve detection should translate into greater efficacy, by ensuring accurate deposition and spread of local anesthetic around the target nerve. The identification of nerve is among the most difficult tasks that anesthetists can encounter in the UGRA procedure...
Large metadata aggregations provide access to documents held by multiple cultural heritage (CH) institutions. As CH institutions encode their metadata using different schemas and follow different data standards, aggregators must process the received data before making it available through a unified portal. Staff members at the contributing CH institutions don't receive feedback regarding the quality...
In complex visual recognition systems, feature fusion has become crucial to discriminate between a large number of classes. In particular, fusing high-level context information with image appearance models can be effective in object/scene recognition. To this end, we develop an auto-context modeling approach under the RKHS (Reproducing Kernel Hilbert Space) setting, wherein a series of supervised...
Similarity measuring plays as an import role in stereo matching, whether for visual data from standard cameras or for those from novel sensors such as Dynamic Vision Sensors (DVS). Generally speaking, robust feature descriptors contribute to designing a powerful similarity measurement, as demonstrated by classic stereo matching methods. However, the kind and representative ability of feature descriptors...
This paper describes a methodology approach and a tool dedicated to the exploration of the Twitter social stream by combining different contextual parameters such as time, keywords, gender or the opinion. The exploration can be made in two main modes depending on the fact that the phenomenon is either known or not. The first mode, similar to the use of Googlefight search engine, allows to compare...
Separate brain regions exhibit synchronous intrinsic activity used to assess connectivity patterns known to appear among brain areas. Connectivity is evaluated from functional magnetic resonance imaging (fMRI) measuring the blood oxygen level dependent signal (BOLD) signal. Extensive research has revealed a distinctive pattern of connectivity among brain areas that can be visualized through a functional...
The correct execution of well-defined movements plays a crucial role in physical rehabilitation and sports. While there is an extensive number of well-established approaches for human action recognition, the task of assessing the quality of actions and providing feedback for correcting inaccurate movements has remained an open issue in the literature. We present a learning-based method for efficiently...
Massive open online courses (MOOCs) have high potential for improving education worldwide, but understanding of student behavior and situations is difficult to achieve in online settings. Network analytics and visualizations can assist instructors with supporting understanding of student behavior as courses unfold. In this work, we perform a visual comparative analysis of two different MOOC courses...
Visual scene understanding has been one of the major goals of computer vision. However, existing work has focused on the object-level understanding, which limits the visual questions that can be answered. The goal of this paper is to invite collective efforts for entity-level understanding of images, by releasing ECO datasets and baselines for this task.
The growth of digital data is tremendous. Any aspect of life and matter is being recorded and stored on cheap disks, either in the cloud, in businesses, or in research labs. We can now afford to explore very complex relationships with many variables playing a part. But for this we need powerful tools that allow us to be creative, to sculpt this intricate insight formulated as models from the raw block...
Intelligence analysts are at the forefront to provide decision makers with a greater picture of current situational context. Their main task is to identify relevant pieces of information from disparate systems and growing amounts of data while often lacking the appropriate tools. We propose a visual analytics approach to support analysts in monitoring and reasoning about the dynamics in a complex...
The current research aims to investigate information visualization found within students' self-regulated learning skills while they are engaged in an interactive learning module. While the cognitive actions represent contextual activities found when students use interactive learning modules, the metacognitive component was represented by planning, monitoring, and regulating strategies. Students at...
This paper presents the design of a new social messaging app for family connection called Kin Circle. From the lens of Interaction Ritual Chains Theory, we argue that interactions among family members through social messaging groups can be seen as successful rituals, which give rise to more rituals that strengthen familial bond. Our previous study of WhatsApp usage among extended family members shows...
Narrative games may offer reasoning on players' behavior or make-believe on players' personation as a pursuit to achieve specific goals. One of the goals is probably the intention to instill learning, which subconsciously provide information on the content of the game. However, there is lack of empirical evidence on game aesthetics for player's perceived learning. By means of expert review, this article...
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