Viewpoint selection by navigation through entropy maps

Arbel, Tal; Ferrie, Frank P.

doi:10.1109/iccv.1999.791227

Cited by 74 publications

(58 citation statements)

References 9 publications

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“…This path is analyzed afterwards to deduce the perception tasks to perform. Let us mention the recent work of Arbel and Ferrie [1] about view point selection. Even if it deals with the quite different problem of object recognition, the approach is interesting.…”

Section: Overviewmentioning

confidence: 99%

Visual Data Fusion for Objects Localization by Active Vision

Flandin

Chaumette

2002

Computer Vision — ECCV 2002

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Section: Overviewmentioning

confidence: 99%

Visual Data Fusion for Objects Localization by Active Vision

Flandin

Chaumette

2002

Computer Vision — ECCV 2002

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“…Solutions to viewpoint selection have been proposed for the problem of modeling a 3D object from range data [32] and from images [33], for object recognition [34], and also for cinematography [35]. In computer graphics, Vázquez et al [20,36] introduced the viewpoint entropy as a measure to automatically compute good viewing positions for polygonal scenes.…”

Section: Information Theory In Imaging and Graphicsmentioning

confidence: 99%

Information Theory in Scientific Visualization

Wang

Shen

2011

Entropy

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In recent years, there is an emerging direction that leverages information theory to solve many challenging problems in scientific data analysis and visualization. In this article, we review the key concepts in information theory, discuss how the principles of information theory can be useful for visualization, and provide specific examples to draw connections between data communication and data visualization in terms of how information can be measured quantitatively. As the amount of digital data available to us increases at an astounding speed, the goal of this article is to introduce the interested readers to this new direction of data analysis research, and to inspire them to identify new applications and seek solutions using information theory.

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“…Koenderink and Doorn [12,13] introduced the idea of aspect graph to partition the viewing regions surrounding an object in 1970s. Arbel et al [14] in 1999 used the entropy map to define a measure of ambiguity for the resulting belief distributions and use offline entropy maps to guide the on-line navigation. After Vázquez et al [2] in 2001 introduced the Viewpoint Entropy (VE), and then, similarly methods were widely used, especially for volume rendering.…”

Section: Introductionmentioning

confidence: 99%

An Introduction to Viewpoint Selection in Volume Visualization

Xu¹,

He²

2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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Abstract-Scientific researches are always accompanied with a large number of complex data. Thus, it is important to view and analysis these data or objects in a much more efficient way. Viewpoint selection can improve both the speed of rendering and the efficiency of data understanding, became a hot topic in research, and is applied to various research areas. Viewpoint selection considerably influences the amount of information contained in the projected images, has been extensively studied in many areas such as: volume rendering, image-based modeling, object recognition, etc. most of the studies utilizing the information theoretical framework. This paper reviews the relevant literatures on this topic by summarizing the development and application of the technology, and put forward some ideas for future development.

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Viewpoint selection by navigation through entropy maps

Cited by 74 publications

References 9 publications

Visual Data Fusion for Objects Localization by Active Vision

Visual Data Fusion for Objects Localization by Active Vision

Information Theory in Scientific Visualization

An Introduction to Viewpoint Selection in Volume Visualization

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