Way‐Finder: guided tours through complex walkthrough models

Andújar, Carlos; Vázquez, Pere‐Pau; Fairén, Marta

doi:10.1111/j.1467-8659.2004.00781.x

Cited by 77 publications

(48 citation statements)

References 16 publications

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“…There is a rich literature in computer graphics and animation about dynamic view selection [20,1,29,9,23]. Applicable techniques range from direct orientation interpolation [20] to complex view planning for complicated 3D scenes.…”

Section: Related Workmentioning

confidence: 99%

“…Applicable techniques range from direct orientation interpolation [20] to complex view planning for complicated 3D scenes. Andujar et al [1] proposed a camera path planning method for walkthrough of complex scene models. Their method is based on identifying the free-space structure of the scene and an entropy-based measurement of the relevance of a viewpoint.…”

Section: Related Workmentioning

confidence: 99%

“…Since their method prefers views from which the visibility of the voxel is proportional to its weight, the voxel with weight 0.7 has to occlude the other voxel to some degree in order to achieve a higher score for their entropy formula. However, these two voxels are readily visible through some views such as V 1 . From this example, we can see that if the visibility of a voxel can be maximized, it does not have to be proportional to its weight.…”

Section: Static View Selectionmentioning

confidence: 99%

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Dynamic View Selection for Time-Varying Volumes

Ji¹,

Shen²

2006

IEEE Trans. Visual. Comput. Graphics

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Abstract-Animation is an effective way to show how time-varying phenomena evolve over time. A key issue of generating a good animation is to select ideal views through which the user can perceive the maximum amount of information from the time-varying dataset. In this paper, we first propose an improved view selection method for static data. The method measures the quality of a static view by analyzing the opacity, color and curvature distributions of the corresponding volume rendering images from the given view. Our view selection metric prefers an even opacity distribution with a larger projection area, a larger area of salient features' colors with an even distribution among the salient features, and more perceived curvatures. We use this static view selection method and a dynamic programming approach to select time-varying views. The time-varying view selection maximizes the information perceived from the time-varying dataset based on the constraints that the time-varying view should show smooth changes of direction and near-constant speed. We also introduce a method that allows the user to generate a smooth transition between any two views in a given time step, with the perceived information maximized as well. By combining the static and dynamic view selection methods, the users are able to generate a time-varying view that shows the maximum amount of information from a time-varying data set.Index Terms-Static view selection, image based method, dynamic view selection, information entropy, optimization.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Static View Selectionmentioning

confidence: 99%

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Dynamic View Selection for Time-Varying Volumes

Ji¹,

Shen²

2006

IEEE Trans. Visual. Comput. Graphics

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“…They adopted the probabilistic roadmap approach to help users avoid unnecessary maneuvers due to collisions with the environment. Andújar et al [2] constructed a cell-and-portal graph using a distance-to-geometry field over a 3D grid. The graph was then used to automatically generate guided tours for a walkthrough model.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Criteria Approach to Camera Motion Design for Volume Data Animation

Hsu

Zhang

2013

IEEE Trans. Visual. Comput. Graphics

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Abstract-We present an integrated camera motion design and path generation system for building volume data animations. Creating animations is an essential task in presenting complex scientific visualizations. Existing visualization systems use an established animation function based on keyframes selected by the user. This approach is limited in providing the optimal in-between views of the data. Alternatively, computer graphics and virtual reality camera motion planning is frequently focused on collision free movement in a virtual walkthrough. For semi-transparent, fuzzy, or blobby volume data the collision free objective becomes insufficient. Here, we provide a set of essential criteria focused on computing camera paths to establish effective animations of volume data. Our dynamic multi-criteria solver coupled with a force-directed routing algorithm enables rapid generation of camera paths. Once users review the resulting animation and evaluate the camera motion, they are able to determine how each criterion impacts path generation. In this paper, we demonstrate how incorporating this animation approach with an interactive volume visualization system reduces the effort in creating context-aware and coherent animations. This frees the user to focus on visualization tasks with the objective of gaining additional insight from the volume data.

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“…The Way-finder system presented by Andújar et al [2004] algorithmically computes an exploration path through a 3D environment. This algorithm is based on a voxelized version of the 3D world, just like the tour generation algorithm presented in this paper, but employs another method to compute a cell and portal graph for use with a backtracking tour generator, whereas our algorithm builds disjoint visibility subsets and performs TSP computations on the resulting connectivity graph.…”

Section: Motion Controlmentioning

confidence: 99%

Tour generation for exploration of 3D virtual environments

Elmqvist

Tudoreanu

Tsigas

2007

Proceedings of the 2007 ACM Symposium on Virtual Reality Software and Technology

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Navigation in complex and large-scale 3D virtual environments has been shown to be a difficult task, imposing a high cognitive load on the user. In this paper, we present a comprehensive method for assisting users in exploring and understanding such 3D worlds. The method consists of two distinct phases: an off-line computation step deriving a grand tour using the world geometry and any semantic target information as input, and an on-line interactive navigation step providing guided exploration and improved spatial perception for the user. The former phase is based on a voxelized version of the geometrical dataset that is used to compute a connectivity graph for use in a TSP-like formulation of the problem. The latter phase takes the output tour from the off-line step as input for guiding 3D navigation through the environment.

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Way‐Finder: guided tours through complex walkthrough models

Cited by 77 publications

References 16 publications

Dynamic View Selection for Time-Varying Volumes

Dynamic View Selection for Time-Varying Volumes

A Multi-Criteria Approach to Camera Motion Design for Volume Data Animation

Tour generation for exploration of 3D virtual environments

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