Glaze: A Visualization Framework for Mobile Devices

Alves, Lunara de Sousa; Nisi, Valentina; Oakley, Ian

doi:10.1007/978-3-642-03655-2_95

Cited by 5 publications

(4 citation statements)

References 5 publications

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“…At the same time, immersive systems isolate a user from its environment in order to ensure that the stimulus reaches more directly, thereby increasing the communicative capacity of the message. On the other hand, the modern Smartphones can make calls, play music, take and store photographs, browse Internet, and of course, they are able to manage and view anywhere the information related to the architectural framework [4].…”

Section: Introductionmentioning

confidence: 99%

Architectural digital images. Quality and emotional evaluation based on the visualization environment

Fonseca

Duran

2011

2011 IEEE Symposium on Computers &Amp; Informatics

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The visualization of architectural images has always been associated with physical models, panels and displays on large format computer screens. However, technological developments in the past decades have produced new interesting devices such as Smartphones or immersive displays. This evolution has created a new workflow that enables on-site management, virtual visualization and decision making through the viewing of information on those devices. In this paper, we will conduct a statistical study to evaluate the emotional differences on visualization architectural images in different environments and the relationship with the quality perceived by the users related with their previously experience in the architectural framework. The results show that factors related to the user such as gender or previous experience with the typology of images, and the type of device, influence the user's emotional reaction.

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Section: Introductionmentioning

confidence: 99%

Architectural digital images. Quality and emotional evaluation based on the visualization environment

Fonseca

Duran

2011

2011 IEEE Symposium on Computers &Amp; Informatics

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“…With mobile GPUs, which are gaining traction lately, more especially among the medical community, there is an increasing demand on transferring computation tasks to mobile devices. As a consequence, several solu- tions have been developed to tackle volume models in such devices [22,14,23,21,27,20]. However, this pushes forward the pressure on data size and the quality of the renderings, and the reduced mobile GPU power further compromises the complexity of the algorithms to be applied to the compressed data.…”

Section: Introductionmentioning

confidence: 99%

Adaptive transfer functions

et al. 2016

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Medical datasets are continuously increasing in size. Although larger models may be available for certain research purposes, in the common clinical practice the models are usually of up to 512×512×2000 voxels. These resolutions exceed the capabilities of conventional GPUs, the ones usually found in the medical doctors' desktop PCs. Commercial solutions typically reduce the data by downsampling the dataset iteratively until it fits the available target specifications. The data loss reduces the visualization quality and this is not commonly compensated with other actions that might alleviate its effects. In this paper we propose Adaptive Transfer Functions, an algorithm that improves the transfer function in downsampled multiresolution models so that the quality of renderings is highly improved. The technique is simple and lightweight, and it is suitable, not only to visualize huge models that would not fit in a GPU, but also to render not-so-large models in mobile GPUs, which are less capable than their desktop counterparts. Moreover, it can also be used to accelerate rendering framerates by using lower levels of the multiresolution hierarchy while still maintaining high quality results in a context and focus approach. We also show an evaluation of these results based on perceptual metrics.

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“…Because of improving mobile devices resources, it supports and adapting all forms of application from computer systems. However mobility and scaled-down technologies lead to some limitations as compare to computer system [2]. Due to these limitations and deficiencies it is not straight forward to adopt or provide available facilities on mobile device as with desktop computers.…”

Section: Introductionmentioning

confidence: 99%

Framework for Interactive Data Mining Results Visualization on Mobile Devices

Khan¹,

Shah²,

Ahmad³

2014

IJDTA

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The rapidly improving technologies like data mining and mobile technology need careful investigation in order to emerge these technologies. In this paper we identified the challenges confront by mobile data mining, visualization challenges, and mobile device limitations. The paper introduced a comprehensive framework that explores the idea, how we can incorporate both of these promising technologies regarding the challenges facing mobile data mining and all possible application scenarios. The paper further specifies the possible ways to merge both of these technologies, with the available resources.

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Glaze: A Visualization Framework for Mobile Devices

Cited by 5 publications

References 5 publications

Architectural digital images. Quality and emotional evaluation based on the visualization environment

Architectural digital images. Quality and emotional evaluation based on the visualization environment

Adaptive transfer functions

Framework for Interactive Data Mining Results Visualization on Mobile Devices

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