Fast and intuitive generation of geometric shape transitions

Zöckler, Malte; Stalling, Detlev; Hege, Hans-Christian

doi:10.1007/pl00013396

Cited by 83 publications

(71 citation statements)

References 21 publications

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“…Existing concepts and techniques aim at morphing one shape into another shape by concentrating on the shape itself, i.e., trying to stretch, compress and bend one shape into another shape over a given time period and in a realistic fashion (e.g., [13][14][15]). These works are not designed for the geographic information (GI) and mapping scientific fields, but rather to real-time virtual reality and animation in general.…”

Section: Related Workmentioning

confidence: 99%

Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization

Dalyot

Doytsher

2013

IJGI

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Visualizing quantitative time-dependent changes in the topography requires relying on a series of discrete given multi-temporal topographic datasets that were acquired on a given time-line. The reality of physical phenomenon occurring during the acquisition times is complex when trying to mutually model the datasets; thus, different levels of spatial inter-relations and geometric inconsistencies among the datasets exist. Any straight forward simulation will result in a truncated, ill-correct and un-smooth visualization. A desired quantitative and qualitative modelling is presumed to describe morphologic changes that occurred, so it can be utilized to carry out more precise and true-to-nature visualization tasks, while trying to best describe the reality transition as it occurred. This research paper suggests adopting a fully automatic hierarchical modelling mechanism, hence implementing several levels of spatial correspondence between the topographic datasets. This quantification is then utilized for the datasets morphing and blending tasks required for intermediate scene visualization. The establishment of a digital model that stores the local spatial transformation parameterization correspondences between the topographic datasets is realized. Along with designated interpolation concepts, this complete process ensures that the visualized transition from one topographic dataset to the other via the quantified correspondences is smooth and continuous, while maintaining morphological and topological relations.

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Section: Related Workmentioning

confidence: 99%

Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization

Dalyot

Doytsher

2013

IJGI

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“…Polygonal representations can be morphed by interpolating the locations of the surface points [4,72,108,189]. Implicit surfaces (i.e.…”

Section: Volume-based As Opposed To Polygon-based or Implicit Morphingmentioning

confidence: 99%

Volume Measurement in Sequential Freehand 3-D Ultrasound

Treece

Prager

Gee

et al. 1999

Lecture Notes in Computer Science

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SummaryThree-dimensional (3D) acquisition and visualisation techniques are increasingly being incorporated into commercial ultrasound scanners. The diagnostic benefit of such techniques is not yet convincing, compared to the added inconvenience of using them. Although it is straightforward to use special probes to acquire 3D data, these are more restrictive than conventional 2D probes. The only 3D technique which retains the scanning flexibility and wide area of application of 2D ultrasound, is freehand 3D ultrasound, where a 2D probe is moved manually and its location sensed remotely. However, it is hard to generate a regular volume of data from the resulting non-parallel ultrasound images.Probably the largest body of evidence justifying the use of 3D ultrasound relates to the accurate measurement of volume. However, volume measurement with 3D ultrasound requires segmentation (i.e. outlining of the area of interest), which is a time consuming, manual task. Both this problem, and that of creating a regular volume of data, are eased by the use of sequential freehand 3D ultrasound, a recent technique amplified in this thesis, where all the processing is performed on the original ultrasound images. Thus a regular array of data is not required, and segmentation is performed on images whose features and artifacts are recognisable to the clinician.In this thesis, novel volume measurement and surface visualisation algorithms are developed for sequential freehand 3D ultrasound. A particular emphasis is placed on limiting the number of segmented cross-sections required for a given measurement accuracy. Inherent accuracy is demonstrated by simulation to be within ±2%, from 10 or fewer cross-sections. In vivo precision, including registration and segmentation errors, is shown to be within ±7%, even on complicated objects such as the liver or a foetus, from similar numbers of cross-sections. The volume can be updated in real-time as each image is segmented, and surfaces can be interpolated and visualised within a few seconds. Such visualisation can reveal errors in the segmentation which are otherwise hard to see.In addition, a framework for multiple-sweep data is developed, which allows volume measurement and surface visualisation of anatomy that can only be scanned by several sweeps of the ultrasound probe. Accurate volume measurements can therefore be made of all areas observable by conventional ultrasound. These measurements can be accomplished within approximately 5 minutes of examining the patient.The surface visualisation algorithms can also produce high quality renderings of data from a wide range of sources in medical imaging and other fields. The interpolation of cross-sections is an improvement on shape-based interpolation, and the triangular mesh created from the data is of a much higher quality than that using marching cubes. An extension of the surface interpolation algorithm can also be used to gradually change, or 'morph' one 3D surface to another, a technique commonly used in the film industry.

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“…Because mesh segmentation is an important step towards model understanding, so it has become a key ingredient in many research problems such as skeleton extraction (Biasotti et al, 2003，Katz andTal, 2003), texture mapping (Sheffer et al, 2006), deformation ， Zockler et al, 2000, simplification (Cohen-Steiner et al, 2004), compression (Zuckerberger et al, 2002), etc.…”

Section: Introductionmentioning

confidence: 99%

Mesh segmentation guided by seed points

Jiao

Zhang

2015

JAMDSM

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Segmenting 3D models into meaningful parts is a fundamental problem in computer graphics. In this paper, we present an algorithm which is guided by the mesh vertices for segmenting a mesh into meaningful sub-meshes. First, a candidate set of feature points is selected to highlight the most significant features of the model. After that, a diversity measure is calculated by using Hausdorff distance. The collection of seed points we defined is a subset of the candidate set. The collection of seed points consists of two parts, namely, the basic point and lucky points. By maximizing the diversity measure between the seed set and candidate set, an appropriate seed point is selected. Based on the collection of seed points, the segmentation process can be guided by these seeds. Because humans generally perceive desirable segmentations at concave regions, and the geodesic distance and curvature are well-known noise sensitive. Considering the above factors, in order to partition the target into meaningful parts, we define a distance function between each pair of mesh vertices. This function is formed by arc length, angular distance and curvature-related correction term. We have tested the method developed in this paper with 3D meshes from the Princeton segmentation benchmark. Moreover, our segmentation method also has been compared with other methods. The experimental results have demonstrated the effectiveness of the proposed segmentation method.

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Fast and intuitive generation of geometric shape transitions

Cited by 83 publications

References 21 publications

Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization

Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization

Volume Measurement in Sequential Freehand 3-D Ultrasound

Mesh segmentation guided by seed points

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