An interactive tool for fitting surfaces to volume data

Sowell, Ross; Liu, Lu; Ju, Tao; Grimm, Cindy

doi:10.1145/1400885.1400967

Cited by 7 publications

(9 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, it only involves contours drawn on different parallel planes along a unique axis. To overcome this limitation, alternatives have been explored but are dedicated to voxel inputs [19].…”

Section: Free-form Objectsmentioning

confidence: 99%

Worm Selector: Volume Selection in a 3D Point Cloud Through Adaptive Modelling

Dubois¹,

Hamelin

2017

IJVR

View full text Add to dashboard Cite

3D point clouds are more and more widely used, especially because of the proliferation of manual and cheap 3D scanners and 3D printers. Due to the large size of the 3D point clouds, selecting part of them is very often required. Existing interaction techniques include ray/cone casting and predefined or free-form selection volume. In order to cope with the traditional trade-off between accuracy, ease of use and flexibility of these different forms of selection techniques in a 3D point cloud, we present the Worm Selector. It allows to select complex shapes while remaining simple to use and accurate. Using the Worm Selector relies on three principles: 1) points are selected by progressively constructing a cylinder-like shape (the adaptative worm) through the sequential definition of several sections; 2) a section is defined as a set of two contours linked together with straight lines; 3) each contour is a freely drawn closed shape. A user study reveals that the Worm Selector is significantly faster than a classical selection mechanism based on predefined volumes such as spheres or cuboids, while maintaining a comparable level of precision and recall.

show abstract

Section: Free-form Objectsmentioning

confidence: 99%

Worm Selector: Volume Selection in a 3D Point Cloud Through Adaptive Modelling

Dubois¹,

Hamelin

2017

IJVR

View full text Add to dashboard Cite

show abstract

“…Cependant cela implique uniquement des contours dessinés sur différents plan parallèles, alignés sur un unique axe. Différentes alternatives ont été explorées [19] pour lever les limites de cette approche mais sont dédiées aux voxels. Le nuage de points a été généré manuellement.…”

Section: Sélection Basée Volumeunclassified

Design and evaluation of an interaction technique for volume selection in a 3D point cloud

Hamelin

Dubois

2015

Proceedings of the 27th Conference on l'Interaction Homme-Machine

View full text Add to dashboard Cite

Une tâche fondamentale d'interaction dans un environnement 3D est la possibilité de réaliser une sélection. Elle est nécessaire pour appliquer des traitements locaux, comme le déplacement d'un objet. Bien que pour les objets larges les techniques classiques fonctionnent bien, comme le lancer de rayon, elles deviennent moins adaptées quand le besoin en précision augmente. Elles sont même impossibles à utiliser pour sélectionner des ensembles de points. Pour ces ensembles de points, nous proposons une nouvelle technique de sélection. Elle permet de sélectionner des formes complexes tout en restant simple d'utilisation. Elle repose sur trois principes : 1) la sélection de points consiste à progressivement élaborer une forme rappelant vaguement un cylindre à travers la définition itérative de sections ; 2) une section est définie par deux contours liés ensemble par des lignes droites ; 3) chaque contour est un tracé fermé dessiné librement. Les résultats d'une évaluation utilisateur établissent que notre technique est significativement plus rapide que les techniques plus classiques basées sur des volumes prédéfinis, comme des sphères ou des cuboïdes, tout en gardant un niveau de précision et de rappel comparable.

show abstract

“…To improve the e ciency of manual segmentations, biologists have tried different methods. For example, VolumeViewer from Sowell et al [26] allows users to draw contours on oblique slicing planes, which helps surface construction for simple shapes but is still not e ective for complex structures. Using the volume intersection technique from Martin and Aggarwal [13] or Space Carving from Kutulakos and Seitz [10], Tay et al [27] drew masks from two orthographic MIP renderings and projected them into 3D to carve a neuron out from their confocal data.…”

Section: Related Workmentioning

confidence: 99%

Interactive extraction of neural structures with user-guided morphological diffusion

Wan

Otsuna

Chien

et al. 2012

2012 IEEE Symposium on Biological Data Visualization (BioVis)

View full text Add to dashboard Cite

Extracting neural structures with their fine details from confocal volumes is essential to quantitative analysis in neurobiology research. Despite the abundance of various segmentation methods and tools, for complex neural structures, both manual and semi-automatic methods are ine ective either in full 3D or when user interactions are restricted to 2D slices. Novel interaction techniques and fast algorithms are demanded by neurobiologists to interactively and intuitively extract neural structures from confocal data. In this paper, we present such an algorithm-technique combination, which lets users interactively select desired structures from visualization results instead of 2D slices. By integrating the segmentation functions with a confocal visualization tool neurobiologists can easily extract complex neural structures within their typical visualization workflow.

show abstract

An interactive tool for fitting surfaces to volume data

Cited by 7 publications

References 3 publications

Worm Selector: Volume Selection in a 3D Point Cloud Through Adaptive Modelling

Worm Selector: Volume Selection in a 3D Point Cloud Through Adaptive Modelling

Design and evaluation of an interaction technique for volume selection in a 3D point cloud

Interactive extraction of neural structures with user-guided morphological diffusion

Contact Info

Product

Resources

About