3D distance fields: a survey of techniques and applications

By Mark W. Jones, J. A. Bærentzen, Milos Srámek. IEEE Transactions on Visualization and Computer Graphics, 2006

455 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/7bc70f23189bf8a5a849ad81a6320948d425418f

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In Aerospace Engineering

In Computer Graphics and Computer-Aided Design

In Computer Vision and Pattern Recognition

Citations in the corpus

An Octree-Based Approach towards Efficient Variational Range Data Fusion (2016, methodology): “We refer the reader to a survey on 3D distance fields as a special variant of level-set functions [10].”
2D Euclidean distance transform algorithms: A comparative survey (2008, methodology): “Section 8 describes the methodology for speed and exactness tests.”
An efficient and parallel level set reinitialization method - Application to micromechanics and microstructural evolutions (2015, methodology): “In [14], a review of various improvements to this method proposed in literature to overcome this difficulty can be found.”
Medical image processing on the GPU - Past, present and future (2013, background): “…of 4, compared to the count and sort approach by Shams et al. (2010a) ) have a long history in the image processing domain and can be used for a wide range of applications (Jones et al., 2006), including the creation of object skeletons and the efficient application of morphological operations.”
On utilizing topology optimization to design support structure to prevent residual stress induced build failure in laser powder bed metal additive manufacturing (2019, methodology): “(A6) can be calculated based on the P-norm proposed in [27] as: ∂σPN ∂?̅?e H = (∑ (?̅?e H)P e=1 ) ( 1 P (?̅?e H)(P−1) (A7)”
GeoS: Geodesic Image Segmentation (2008, background): “Excellent surveys of techniques for computing non-geodesic distance transforms may be found in [14,15].”
Neural Unsigned Distance Fields for Implicit Function Learning (2020, background): “Distance fields can be found in computer vision, graphics, robotics and physics [37].”
Motion Capture of Hands in Action Using Discriminative Salient Points (2012, methodology): “Collisions are then penalized using distance fields [31].”