Efficient feature-preserving local projection operator for geometry reconstruction

Liao, Bin; Xiao, Chunxia; Jin, Liqiang; Fu, Hongbo

doi:10.1016/j.cad.2013.02.003

Cited by 46 publications

(29 citation statements)

References 33 publications

(101 reference statements)

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“…We will show that this concept is compatible with our continuous LOP formulation and can be adopted without any additional effort. Kernel LOP (KLOP) [Liao et al 2013] reduces the computation cost of LOP by subsampling the point cloud using a kernel density estimate (KDE). While this reduction achieves a decent acceleration, reducing the number of discrete input samples also constrains the number of usable resampling particles [Lipman et al 2007], thus the general reconstruction quality deteriorates quickly for a small number of kernels.…”

Section: Lop and Variantsmentioning

confidence: 99%

“…To be able to fully assess the performance of our system, we do not currently exploit any frame-to-frame coherence. However, common temporal-coherence approaches could accelerate our system even further [Liao et al 2013]. Note that for normal estimation, we simply orient the normals towards the camera when rendering the reconstructed point cloud.…”

Section: Performancementioning

confidence: 99%

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Continuous projection for fast L ₁ reconstruction

et al. 2014

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On this mixture, a Continuous Projection operator is applied, which efficiently produces an L1 reconstruction of 72K point positions (c) at ∼ 9 FPS. In contrast, an L2 reconstruction (d) with small feature-preserving kernel exhibits heavily visible noise (top), while a larger kernel biases and oversmoothes the result (bottom). Our method runs at up to 7 times the speed of a fast GPU implementation of standard WLOP while providing comparable or even better quality, allowing for interactive robust reconstruction of unordered dynamic point sets. AbstractWith better and faster acquisition devices comes a demand for fast robust reconstruction algorithms, but no L1-based technique has been fast enough for online use so far. In this paper, we present a novel continuous formulation of the weighted locally optimal projection (WLOP) operator based on a Gaussian mixture describing the input point density. Our method is up to 7 times faster than an optimized GPU implementation of WLOP, and achieves interactive frame rates for moderately sized point clouds. We give a comprehensive quality analysis showing that our continuous operator achieves a generally higher reconstruction quality than its discrete counterpart. Additionally, we show how to apply our continuous formulation to spherical mixtures of normal directions, to also achieve a fast robust normal reconstruction.

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Section: Lop and Variantsmentioning

confidence: 99%

Section: Performancementioning

confidence: 99%

Continuous projection for fast L ₁ reconstruction

et al. 2014

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“…Although we inherit the limitations discussed in section 6, we believe our method has the potential to benefit the skeleton extraction research of animated surfaces. In the future, we will apply the proposed method to the geometry reconstruction and editing of time‐varying surfaces .…”

Section: Resultsmentioning

confidence: 99%

Effective skeletons extraction for animated surfaces based on geometry propagation

Pang

Zhao

Xiao

2015

Computer Animation & Virtual

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We introduce a registration-based propagation strategy to extract temporally coherent skeletons from the animated surfaces. We first extract complete skeletons for the key frames of the animated surfaces, and present a spatio-temporal L 1 -medial skeleton extraction method to extract the initial skeletons for the immediate frames between the key frames. As these initial skeletons may not be complete, we then develop a global skeleton alignment method, which effectively warps the key skeleton to these initial skeletons subsequently. By using the geometry merging, we propagate the geometry of the warped key skeleton to the initial skeletons, and produce temporally coherent skeletons for the input animated surfaces. Our system can be applied to the raw scanned animated object and requires only minimal user interaction to extract complete and temporally coherent animated skeletons.

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“…Locally Optimal Projector (LOP) related methods (Huang et al, 2009(Huang et al, , 2013Liao et al, 2013;Lipman et al, 2007;Preiner et al, 2014) have recently attracted much attention for its robustness against outliers. The core of LOP operator is to project an arbitrary number of particles to a point set to represent the local L 1 median of the original point set.…”

Section: Related Workmentioning

confidence: 99%