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Inferring 3D structure with a statistical image-based shape model
2003
Proceedings Ninth IEEE International Conference on Computer Vision
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The 3D shape of a class of objects may be represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. ...
Bayesian reconstructions of new shapes can then be estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. ...
A probabilistic "shape+structure" model is formed using a probability density of multi-view silhouette images augmented with known 3D structure parameters. ...
doi:10.1109/iccv.2003.1238408
dblp:conf/iccv/GraumanSD03
fatcat:a3a2g3ubxzfcfp3hl4p7lo45jq
3D Motion Tracking Based on Probabilistic Volumetric Reconstruction and Optical Flow
2010
2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images
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This paper proposes a method for motion tracking of objects without a pre-defined shape, the main aspect of this method is the use of a probabilistic volumetric reconstruction that incorporates motion ...
It was noted that the proposed information of velocity vector fields are a good option to improve the perception of motion in 3D reconstruction, providing the best results in the tracking. ...
of dealing with a image sequence (all pixels) and get an answer as 2D velocity field, a sequence of voxel sets are used, and a 3D velocity field is obtained. ...
doi:10.1109/sibgrapi.2010.58
dblp:conf/sibgrapi/SimasFNBB10
fatcat:7jmwxw6upnfxtmw33pxv5k2hda
Visual exploration of HARDI fibers with probabilistic tracking
2016
Information Sciences
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Therefore, the proposed approach shows not only the shape but also the confidence of the fiber paths. ...
Then the user can further refine fiber bundle selection using probabilistic information from the pixel bars. ...
Related Work Tensor glyphs represent the local diffusion information by the shape and orientation of their geometry [35] . ...
doi:10.1016/j.ins.2015.04.045
fatcat:k262zjalwfhqpikbygpnwkq3xe
Grasp Exploration for 3D Object Shape Representation Using Probabilistic Map
[chapter]
2010
IFIP Advances in Information and Communication Technology
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Electromagnetic motion tracking sensors are used on the fingers for object contour following to acquire the 3D points to represent its shape using a probabilistic volumetric map. ...
In this work it is shown the representation of 3D object shape acquired from grasp exploration. ...
We have considered all cells with probability higher than 0.7 to represents the object shape. ...
doi:10.1007/978-3-642-11628-5_23
fatcat:gco264sfdzb7rhrumuhzahk2oq
Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model
2010
Medical Physics (Lancaster)
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These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. ...
In the second stage, a deformable surface evolves towards the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model ...
this section, we briefly describe a method for establishing correspondences across shapes represented by 3D triangular meshes. ...
doi:10.1118/1.3315367
pmid:20443479
fatcat:jwlytndhajac7gpnkmrwyut7fu
An Efficient Probabilistic Registration Based on Shape Descriptor for Heritage Field Inspection
2020
ISPRS International Journal of Geo-Information
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We developed a novel shape descriptor based on a local frame of principal directions. ...
Within the frame, its density and distance feature images were generated to describe the shape of the local surface. ...
Next, we calculate the distance and density features of each grid to form shape images. ...
doi:10.3390/ijgi9120759
fatcat:opnxzcfnmrfjlnb4kev3edyx2u
Probabilistic reasoning for assembly-based 3D modeling
2011
ACM SIGGRAPH 2011 papers on - SIGGRAPH '11
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The probabilistic model is used to present components that are semantically and stylistically compatible with the 3D model that is being assembled. ...
Figure 1 : 3D models created with our assembly-based 3D modeling tool. Abstract Assembly-based modeling is a promising approach to broadening the accessibility of 3D modeling. ...
The probabilistic model of Merrell et al. is designed specifically to represent architectural programs. We introduce a probabilistic model for the structure of general 3D shapes. ...
doi:10.1145/1964921.1964930
fatcat:mteprtr3vrawvfg4qlcxu76vaq
Probabilistic reasoning for assembly-based 3D modeling
2011
ACM Transactions on Graphics
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The probabilistic model is used to present components that are semantically and stylistically compatible with the 3D model that is being assembled. ...
Figure 1 : 3D models created with our assembly-based 3D modeling tool. Abstract Assembly-based modeling is a promising approach to broadening the accessibility of 3D modeling. ...
The probabilistic model of Merrell et al. is designed specifically to represent architectural programs. We introduce a probabilistic model for the structure of general 3D shapes. ...
doi:10.1145/2010324.1964930
fatcat:4qyx4il37bgmdikboxcmepgc6y
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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DeepSDF, like its classical counterpart, represents a shape's surface by a continuous volumetric field: the magnitude of a point in the field represents the distance to the surface boundary and the sign ...
Figure 1 : DeepSDF represents signed distance functions (SDFs) of shapes via latent code-conditioned feed-forward decoder networks. ...
Our contributions include: (i) the formulation of generative shape-conditioned 3D modeling with a continuous implicit surface, (ii) a learning method for 3D shapes based on a probabilistic auto-decoder ...
doi:10.1109/cvpr.2019.00025
dblp:conf/cvpr/ParkFSNL19
fatcat:6wnfa36lqvbxdbnrc3het6mfbe
Shape- and Pose-Invariant Correspondences Using Probabilistic Geodesic Surface Embedding
[chapter]
2011
Lecture Notes in Computer Science
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We represent objects as triangular meshes and consider normalized geodesic distances as representing their intrinsic characteristics. ...
We present a method for automatically finding such correspondences that deals with significant variations in pose, shape and resolution between pairs of objects. ...
Learning the parameters of our CRF model from training data is another direction for future work. Fig. 2 . 2 Conditional Random Field (CRF) model for finding correspondences. ...
doi:10.1007/978-3-642-23123-0_26
fatcat:aawvysb3nzfbnkpd5mx2lvuteq
Detecting Dead Standing Eucalypt Trees from Voxelised Full-Waveform Lidar Using Multi-Scale 3D-Windows for Tackling Height and Size Variations
2020
Forests
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Eucalypt treeshave irregular shapes making delineation of them challenging. Additionally, since the study area is anative forest, trees significantly vary in terms of height, density and size. ...
Both thesingle 3D-windows approach and the new multi-scale 3D-windows approach were implementedfor comparison purposes. ...
Furthermore, they are spatially well-distributed and represent the entire study area; the minimum distance between two field plots was 3.1 km and the average distance between a plot and its nearest one ...
doi:10.3390/f11020161
fatcat:jifvojwgqrgmxlzsk6xfqxeqam
Three-Dimensional Maps of All Chromosomes in Human Male Fibroblast Nuclei and Prometaphase Rosettes
2005
PLoS Biology
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Radial distance measurements showed a probabilistic, highly nonrandom correlation with chromosome size: small chromosomes-independently of their gene density-were distributed significantly closer to the ...
Modeling of 3D CT arrangements suggests that cell-type-specific differences in radial CT arrangements are not solely due to geometrical constraints that result from nuclear shape differences. ...
We thank Marion Cremer for kindly contributing her 3D analysis of radial HSA 18 and 19 CT arrangements in nuclei of cycling amniotic fluid cells ( Figure S8D ...
doi:10.1371/journal.pbio.0030157
pmid:15839726
pmcid:PMC1084335
fatcat:2vin7s2f6jfublg5gt7u23wfz4
Single-view Object Shape Reconstruction Using Deep Shape Prior and Silhouette
[article]
2019
arXiv
pre-print
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Our framework employs a deep autoencoder to learn a set of latent codes of 3D object shapes, which are fitted by a probabilistic shape prior using Gaussian Mixture Model (GMM). ...
3D shape reconstruction from a single image is a highly ill-posed problem. ...
We train this autoencoder using 3D Chamfer Distance as defined below: L To learn a probabilistic model as the shape prior, we fit a GMM to the learned latent space. ...
arXiv:1811.11921v2
fatcat:kozp53b3cfh7xdtlmyan57djva
Probabilistic representation of 3D object shape by in-hand exploration
2010
2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
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This work presents a representation of 3D object shape using a probabilistic volumetric map derived from inhand exploration. ...
The 3D object probabilistic representation can be used in several applications related with grasp generation tasks. ...
Probabilistic Volumetric Map Occupancy Estimation In our previous work [15] , a probabilistic map was developed to represent objects shapes through grasp exploration, but with many limitations. ...
doi:10.1109/iros.2010.5649286
dblp:conf/iros/FariaMLD10
fatcat:elhwkhom6zg2dg5w3iaqhxpjmm
Construction of Circular Quadrature Amplitude Modulations (CQAM)
2018
2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)
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Circular quadrature amplitude modulations (CQAM) are introduced as an alternative to mono-dimensional ASK constellations (and their QAM Cartesian product) for probabilistic shaping with non-binary error-correcting ...
PROBABILISTIC SHAPING FOR NON-BINARY CODES All types of digital transmission systems combining errorcorrecting codes and probabilistic shaping of the modulator constellation can be represented by the model ...
This paper deals with the construction of signal constellations for probabilistic shaping. ...
doi:10.1109/icsee.2018.8646035
fatcat:y7dkanbtivhojktbkpbstbqfci
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