Smart cities can generate a lot of useful data for analyzing behavior and infrastructures, helping with urban planning. However, the applications found are often limited to desktop viewing only, which can hinder or restrict data analysis. This work proposes an immersive data visualization of the population of medical centers to assist in the analysis and development of new strategies to deal with overcrowding situations. The prototype allows the visualization of crowd data located in places of interest on top of a 3D map. The user can view the number of people present at the location at the current stage of the simulation or over time. To test the prototype, data from an infectious disease simulator was used, called LODUS. The results showed that the application has potential for visualizing this type of data.

Television and live internet broadcasts coexist with a stream of social network commentary, engaging audiences in more complex ways than traditional ratings can represent, demanding convergent tools to analyze such contemporary media. In this work, we present PeakVis, an interactive tool that syncs a video recording with a responsive line graph representing the total number of tweets from each moment, the top messages, a dynamic word cloud, and a semantic graph showing word correlation. Thus, this novel interactive approach allows the analysis of broadcast highlights identified through Twitter posts peaks. We explored this freely available tool’s applicability by analyzing two different case studies: the season finale of a reality show and the final episode of a telenovela. We could observe that it allows us to quickly identify the most relevant segments and grasp the discussed subjects in-depth through the obtained results, showing its value in broadcast analysis.

Nowadays there are more than 250 million visually-impaired people worldwide and mobility autonomy in outdoor environments is perhaps the greatest challenge they have to face. More specifically, crossing the street with no human aid is an open problem, since the majority of the pedestrian traffic lights in underdeveloped countries do not provide sound aids. There are very few studies addressing the detection of pedestrian traffic lights based on images acquired by mobile devices, and to the best of our knowledge there is a clear gap in the literature regarding the use of recent state-of-the-art computer vision approaches such as deep neural networks for addressing such a problem. In this paper, we investigate the current state-of-the-art in localization/detection and classification based on deep neural networks, and we present a solution for the detection of pedestrian traffic lights together with their current state for helping visually-impaired people to cross the streets with the aid of their mobile devices. For such, we provide a novel public dataset with 4,399 labeled images of pedestrian traffic lights and we present a detailed comparison among the state-of-the-art methods for classification and localization/detection. We show empirical evidence regarding the feasibility of embedding our approach in mobile devices so it can be used by people with visual impairment.

The amount of data generated worldwide associated with geolocalization has exponentially increased over the last decade due to social networks, population demographics, and the popularization of Global Positioning Systems. Several methods for geovisualization have already been developed, but many of them are focused on a specific application or require learning a variety of tools and programming languages. It becomes even more difficult when users have to manage a large amount of data because state-of-the-art alternatives require the use of third-party pre-processing tools. We present a novel Domain-Specific Language (DSL), which focuses on large data geovisualizations. Through a compiler, we support automatic visualization generations and data pre-processing. The system takes advantage of multi-core parallelism to speed-up data pre-processing abstractly. Our experiments were designated to highlight the programming effort and performance of our DSL. The results have shown a considerable programming effort reduction and efficient parallelism support with respect to the sequential version.

Data visualization is an alternative for representing information and helping people gain faster insights. However, the programming/creating of a visualization for large data sets is still a challenging task for users with low-level of software development knowledge. Our goal is to increase the productivity of experts who are familiar with the application domain. Therefore, we proposed an external Domain-Specific Language (DSL) that allows massive input of raw data and provides a small dictionary with suitable data visualization keywords. Also, we implemented it to support efficient data filtering operations and generate HTML or Javascript output code files (using Google Maps API). To measure the potential of our DSL, we evaluated four types of geospatial data visualization maps with four different technologies. The experiment results demonstrated a productivity gain when compared to the traditional way of implementing (e.g., Google Maps API, OpenLayers, and Leaflet), and efficient algorithm implementation.

Printing web pages is usually a thankless task as the result is often a document with many badly-used pages and poor layout. Besides the actual content, superfluous web elements like menus and links are often present and in a printed version they are commonly perceived as an annoyance. Therefore, a solution for obtaining cleaner versions for printing is to detect parts of the page that the reader wants to consume, eliminating unnecessary elements and filtering the "true" content of the web page. In addition, the same solution may be used online to present cleaner versions of web pages, discarding any elements that the user wishes to avoid.

Marketing flyers, greeting cards, brochures and similar materials are expensive to produce, since these documents need to be personalized and typically require a graphic design professional to create. Either authoring tools are too complex to use or a predefined set of fixed templates is available, which can be restrictive and difficult to produce the desired results. Thus, simpler design tools are a compelling need for small businesses and consumers. This paper describes an interactive authoring method for creating free-form documents based on a force-directed approach, traditionally applied for graph layout problems. This is used for automatically distributing and manipulating images, text and decorative elements on a page, according to forces modeled after physical laws. Such approach can be used for enabling easy authoring of personalized brochures, photo albums, calendars, greeting cards and other free-form documents. A prototype has been developed for evaluation purposes, and is briefly described in this paper. Evaluation results are presented as well, showing that users enjoy the experience of designing a page by interacting with it, and that end results can be satisfactory.

This paper introduces two methods for measuring the alignment of items on a page with respect to its left/right margins. The methods are based on the path followed by the eyes as they follow the items from top to bottom of the page.