16,812 research outputs found
Creating Simplified 3D Models with High Quality Textures
This paper presents an extension to the KinectFusion algorithm which allows
creating simplified 3D models with high quality RGB textures. This is achieved
through (i) creating model textures using images from an HD RGB camera that is
calibrated with Kinect depth camera, (ii) using a modified scheme to update
model textures in an asymmetrical colour volume that contains a higher number
of voxels than that of the geometry volume, (iii) simplifying dense polygon
mesh model using quadric-based mesh decimation algorithm, and (iv) creating and
mapping 2D textures to every polygon in the output 3D model. The proposed
method is implemented in real-time by means of GPU parallel processing.
Visualization via ray casting of both geometry and colour volumes provides
users with a real-time feedback of the currently scanned 3D model. Experimental
results show that the proposed method is capable of keeping the model texture
quality even for a heavily decimated model and that, when reconstructing small
objects, photorealistic RGB textures can still be reconstructed.Comment: 2015 International Conference on Digital Image Computing: Techniques
and Applications (DICTA), Page 1 -
BSP-fields: An Exact Representation of Polygonal Objects by Differentiable Scalar Fields Based on Binary Space Partitioning
The problem considered in this work is to find a dimension independent algorithm for the generation of signed scalar fields exactly representing polygonal objects and satisfying the following requirements: the defining real function takes zero value exactly at the polygonal object boundary; no extra zero-value isosurfaces should be generated; C1 continuity of the function in the entire domain. The proposed algorithms are based on the binary space partitioning (BSP) of the object by the planes passing through the polygonal faces and are independent of the object genus, the number of disjoint components, and holes in the initial polygonal mesh. Several extensions to the basic algorithm are proposed to satisfy the selected optimization criteria. The generated BSP-fields allow for applying techniques of the function-based modeling to already existing legacy objects from CAD and computer animation areas, which is illustrated by several examples
Gap Processing for Adaptive Maximal Poisson-Disk Sampling
In this paper, we study the generation of maximal Poisson-disk sets with
varying radii. First, we present a geometric analysis of gaps in such disk
sets. This analysis is the basis for maximal and adaptive sampling in Euclidean
space and on manifolds. Second, we propose efficient algorithms and data
structures to detect gaps and update gaps when disks are inserted, deleted,
moved, or have their radius changed. We build on the concepts of the regular
triangulation and the power diagram. Third, we will show how our analysis can
make a contribution to the state-of-the-art in surface remeshing.Comment: 16 pages. ACM Transactions on Graphics, 201
Morphing of Triangular Meshes in Shape Space
We present a novel approach to morph between two isometric poses of the same
non-rigid object given as triangular meshes. We model the morphs as linear
interpolations in a suitable shape space . For triangulated 3D
polygons, we prove that interpolating linearly in this shape space corresponds
to the most isometric morph in . We then extend this shape space
to arbitrary triangulations in 3D using a heuristic approach and show the
practical use of the approach using experiments. Furthermore, we discuss a
modified shape space that is useful for isometric skeleton morphing. All of the
newly presented approaches solve the morphing problem without the need to solve
a minimization problem.Comment: Improved experimental result
3D Shape Segmentation with Projective Convolutional Networks
This paper introduces a deep architecture for segmenting 3D objects into
their labeled semantic parts. Our architecture combines image-based Fully
Convolutional Networks (FCNs) and surface-based Conditional Random Fields
(CRFs) to yield coherent segmentations of 3D shapes. The image-based FCNs are
used for efficient view-based reasoning about 3D object parts. Through a
special projection layer, FCN outputs are effectively aggregated across
multiple views and scales, then are projected onto the 3D object surfaces.
Finally, a surface-based CRF combines the projected outputs with geometric
consistency cues to yield coherent segmentations. The whole architecture
(multi-view FCNs and CRF) is trained end-to-end. Our approach significantly
outperforms the existing state-of-the-art methods in the currently largest
segmentation benchmark (ShapeNet). Finally, we demonstrate promising
segmentation results on noisy 3D shapes acquired from consumer-grade depth
cameras.Comment: This is an updated version of our CVPR 2017 paper. We incorporated
new experiments that demonstrate ShapePFCN performance under the case of
consistent *upright* orientation and an additional input channel in our
rendered images for encoding height from the ground plane (upright axis
coordinate values). Performance is improved in this settin
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