97,823 research outputs found
Constructive 3D Visualization techniques on Mobile platform- Empirical Analysis
As per the concept of 3D visualization on mobile devices it is clear that it belongs to two approaches i.e. local and remote approach. According to the technological advances in mobile devices it is possible to handle some complex data locally and visualized it. But still it is a challenging task to manage real entities on mobile devices locally. Remote visualization plays a vital role for 3D visualization on mobile platform in which data comes from server. Remote approach for 3D visualization on mobile platform consist of various techniques, critical analysis of such techniques is focus into this paper. Also the main focus is on network aspects
Management of spatial data for visualization on mobile devices
Vector-based mapping is emerging as a preferred format in Location-based
Services(LBS), because it can deliver an up-to-date and interactive map visualization.
The Progressive Transmission(PT) technique has been developed to
enable the ecient transmission of vector data over the internet by delivering
various incremental levels of detail(LoD). However, it is still challenging to apply
this technique in a mobile context due to many inherent limitations of mobile
devices, such as small screen size, slow processors and limited memory. Taking
account of these limitations, PT has been extended by developing a framework of
ecient data management for the visualization of spatial data on mobile devices.
A data generalization framework is proposed and implemented in a software
application. This application can signicantly reduce the volume of data for
transmission and enable quick access to a simplied version of data while preserving
appropriate visualization quality. Using volunteered geographic information
as a case-study, the framework shows
exibility in delivering up-to-date spatial
information from dynamic data sources.
Three models of PT are designed and implemented to transmit the additional
LoD renements: a full scale PT as an inverse of generalisation, a viewdependent
PT, and a heuristic optimised view-dependent PT. These models are
evaluated with user trials and application examples. The heuristic optimised
view-dependent PT has shown a signicant enhancement over the traditional PT
in terms of bandwidth-saving and smoothness of transitions.
A parallel data management strategy associated with three corresponding
algorithms has been developed to handle LoD spatial data on mobile clients.
This strategy enables the map rendering to be performed in parallel with a process
which retrieves the data for the next map location the user will require. A viewdependent
approach has been integrated to monitor the volume of each LoD for
visible area. The demonstration of a
exible rendering style shows its potential
use in visualizing dynamic geoprocessed data. Future work may extend this
to integrate topological constraints and semantic constraints for enhancing the
vector map visualization
Open Source Spatial Database for Mobile Devices
This paper presents a system for the management of spatial databases for mobile devices. The wireless internet and mobile computing are the two quickly developed technologies with more and more mobile based services go through the personal and business life. So Spatial data on mobile devices has received a munificent improvement, due to rising the use of PDAs and cellular phones. The technological potential of Mobile Spatial Interaction (MSI), Mobile Human-Computer Interaction requires a conception of visualization possibilities for spatially referenced content and application programs make devices to able to move themselves between different hosts on the network
Wavelet Menus: A Stacking Metaphor for Adapting Marking Menus to Mobile Devices
4 pagesInternational audienceExploration and navigation in multimedia data hierarchies (e.g., photos, music) are frequent tasks on mobile devices. However, visualization and interaction are impoverished due to the limited size of the screen and the lack of precise input devices. As a result, menus on mobile devices do not provide efficient navigation as compared to many innovative menu techniques proposed for Desktop platforms. In this paper, we present Wavelet, the adaptation of the Wave menu for the navigation in multimedia data on iPhone. Its layout, based on an inverted representation of the hierarchy, is particularly well adapted to mobile devices. Indeed, it guarantees that submenus are always displayed on the screen and it supports efficient navigation by providing previsualization of the submenus
Analysis of Information Visualization Techniques for Abstract data on Mobile Devices
To perform visualization on mobile devices different types of data may use like text, picture, maps, physical objects, abstract data etc. According to data visualization is categorized in two areas of visualization that is, scientific visualization and information visualization. Scientific visualization refers to some specific type of data like physical data and it is used for computer modeling and simulation. Information visualization refers to abstract data and used in business and finance, administration, digital media and other abstract concepts. The physical and abstract data is only one classification but there are others classification like static and dynamic data, structured and unstructured data, or hierarchical and non-hierarchical data classification. This paper is focus on information visualization of abstract data on mobile devices
Doctor of Philosophy
dissertationRecent advancements in mobile devices - such as Global Positioning System (GPS), cellular phones, car navigation system, and radio-frequency identification (RFID) - have greatly influenced the nature and volume of data about individual-based movement in space and time. Due to the prevalence of mobile devices, vast amounts of mobile objects data are being produced and stored in databases, overwhelming the capacity of traditional spatial analytical methods. There is a growing need for discovering unexpected patterns, trends, and relationships that are hidden in the massive mobile objects data. Geographic visualization (GVis) and knowledge discovery in databases (KDD) are two major research fields that are associated with knowledge discovery and construction. Their major research challenges are the integration of GVis and KDD, enhancing the ability to handle large volume mobile objects data, and high interactivity between the computer and users of GVis and KDD tools. This dissertation proposes a visualization toolkit to enable highly interactive visual data exploration for mobile objects datasets. Vector algebraic representation and online analytical processing (OLAP) are utilized for managing and querying the mobile object data to accomplish high interactivity of the visualization tool. In addition, reconstructing trajectories at user-defined levels of temporal granularity with time aggregation methods allows exploration of the individual objects at different levels of movement generality. At a given level of generality, individual paths can be combined into synthetic summary paths based on three similarity measures, namely, locational similarity, directional similarity, and geometric similarity functions. A visualization toolkit based on the space-time cube concept exploits these functionalities to create a user-interactive environment for exploring mobile objects data. Furthermore, the characteristics of visualized trajectories are exported to be utilized for data mining, which leads to the integration of GVis and KDD. Case studies using three movement datasets (personal travel data survey in Lexington, Kentucky, wild chicken movement data in Thailand, and self-tracking data in Utah) demonstrate the potential of the system to extract meaningful patterns from the otherwise difficult to comprehend collections of space-time trajectories
AN INTERACTIVE REMOTE VISUALIZATION SYSTEM FOR MOBILE APPLICATION ACCESS
This paper introduces a remote visualization approach that enables the visualization of data sets on mobile devices or in web environments. With this approach the necessary computing power can be outsourced to a server environment. The developed system allows the rendering of 2D and 3D graphics on mobile phones or web browsers with high quality independent of the size of the original data set. Compared to known terminal server or other proprietary remote systems our approach offers a very simple way to integrate with a large variety of applications which makes it useful for real-life application scenarios in business processes
Volumetric Medical Images Visualization on Mobile Devices
Volumetric medical images visualization is an important tool in the diagnosis
and treatment of diseases. Through history, one of the most dificult
tasks for Medicine Specialists has been the accurate location of broken bones
and of the damaged tissues during Chemotherapy treatment, among other
applications; like techniques used in Neurological Studies. Thus these situations
enhance the need of visualization in Medicine. New technologies,
the improvement and development of new hardware as well as software and
the updating of old ones for graphic applications have resulted in specialized
systems for medical visualization. However the use of these techniques
in mobile devices has been poor due to its low performance. In our work,
we propose a client-server scheme, where the model is compressed in the
server side and is reconstructed in a nal thin-client device. The technique
restricts the natural density values to achieve good bone visualization in
medical models, transforming the rest of the data to zero. Our proposal
uses a tridimensional Haar Wavelet Function locally applied inside units
blocks of 16x16x16, similar to the Wavelet Based 3D Compression Scheme
for Interactive Visualization of Very Large Volume Data approach. We also
implement a quantization algorithm which handles error coeficients according
to the frequency distributions of these coe cients. Finally, we made
an evaluation of the volume visualization; on current mobile devices .We
present the speci cations for the implementation of our technique in the
Nokia n900 Mobile Phone
Health Figures: An Open Source JavaScript Library for Health Data Visualization
The way we look at data has a great impact on how we can understand it,
particularly when the data is related to health and wellness. Due to the
increased use of self-tracking devices and the ongoing shift towards preventive
medicine, better understanding of our health data is an important part of
improving the general welfare of the citizens. Electronic Health Records,
self-tracking devices and mobile applications provide a rich variety of data
but it often becomes difficult to understand. We implemented the hFigures
library inspired on the hGraph visualization with additional improvements. The
purpose of the library is to provide a visual representation of the evolution
of health measurements in a complete and useful manner. We researched the
usefulness and usability of the library by building an application for health
data visualization in a health coaching program. We performed a user evaluation
with Heuristic Evaluation, Controlled User Testing and Usability
Questionnaires. In the Heuristics Evaluation the average response was 6.3 out
of 7 points and the Cognitive Walkthrough done by usability experts indicated
no design or mismatch errors. In the CSUQ usability test the system obtained an
average score of 6.13 out of 7, and in the ASQ usability test the overall
satisfaction score was 6.64 out of 7. We developed hFigures, an open source
library for visualizing a complete, accurate and normalized graphical
representation of health data. The idea is based on the concept of the hGraph
but it provides additional key features, including a comparison of multiple
health measurements over time. We conducted a usability evaluation of the
library as a key component of an application for health and wellness
monitoring. The results indicate that the data visualization library was
helpful in assisting users in understanding health data and its evolution over
time.Comment: BMC Medical Informatics and Decision Making 16.1 (2016
Visualization of mobile mapping data via parallax scrolling
Visualizing big point-clouds, such as those derived from mobile mapping data, is not an easy task. Therefore many approaches have been proposed, based on either reducing the overall amount of data or the amount of data that is currently displayed to the user. Furthermore, an entirely free navigation within such a point-cloud is also not always intuitive using the usual input devices. This work proposes a visualization scheme for massive mobile mapping data inspired by a multiplane camera model also known as parallax scrolling. This technique, albeit entirely two-dimensional, creates a depth illusion by moving a number of overlapping partially transparent image layers at various speeds. The generation of such layered models from mobile mapping data greatly reduces the amount of data up to about 98% depending on the used image resolution. Finally, it is well suited for the panoramic-fashioned visualization of the environment of a moving car
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