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Long Chen

Publications and source records attributed to Long Chen.

At least 631 records · Page 35Linked to original sources
arXiv2017

Real-time Geometry-Aware Augmented Reality in Minimally Invasive Surgery

The potential of Augmented Reality (AR) technology to assist minimally invasive surgeries (MIS) lies in its computational performance and accuracy in dealing with challenging MIS scenes. Even with the latest hardware and software technologies, achieving both real-time and accurate augmented information overlay in MIS is still a formidable task. In this paper, we present a novel real-time AR framework for MIS that achieves interactive geometric aware augmented reality in endoscopic surgery with stereo views. Our framework tracks the movement of the endoscopic camera and simultaneously reconstructs a dense geometric mesh of the MIS scene. The movement of the camera is predicted by minimising the re-projection error to achieve a fast tracking performance, while the 3D mesh is incrementally built by a dense zero mean normalised cross correlation stereo matching method to improve the accuracy of the surface reconstruction. Our proposed system does not require any prior template or pre-operative scan and can infer the geometric information intra-operatively in real-time. With the geometric information available, our proposed AR framework is able to interactively add annotations, localisation of tumours and vessels, and measurement labelling with greater precision and accuracy compared with the state of the art approaches.

cs.CV↗
arXiv2017

Video Question Answering via Attribute-Augmented Attention Network Learning

Video Question Answering is a challenging problem in visual information retrieval, which provides the answer to the referenced video content according to the question. However, the existing visual question answering approaches mainly tackle the problem of static image question, which may be ineffectively for video question answering due to the insufficiency of modeling the temporal dynamics of video contents. In this paper, we study the problem of video question answering by modeling its temporal dynamics with frame-level attention mechanism. We propose the attribute-augmented attention network learning framework that enables the joint frame-level attribute detection and unified video representation learning for video question answering. We then incorporate the multi-step reasoning process for our proposed attention network to further improve the performance. We construct a large-scale video question answering dataset. We conduct the experiments on both multiple-choice and open-ended video question answering tasks to show the effectiveness of the proposed method.

cs.CV↗
arXiv2017

High Thermoelectric Figure of Merit by Resonant Dopant in Half-Heusler Alloys

Half-Heusler alloys have been one of the benchmark high temperature thermoelectric materials owing to their thermal stability and promising figure of merit ZT. Simonson et al. early showed that small amounts of vanadium doped in Hf0.75Zr0.25NiSn enhanced the Seebeck coefficient and correlated the change with the increased density of states near the Fermi level. We herein report a systematic study on the role of vanadium (V), niobium (Nb), and tantalum (Ta) as prospective resonant dopants in enhancing the ZT of n-type half-Heusler alloys based on Hf0.6Zr0.4NiSn0.995Sb0.005. The V doping was found to increase the Seebeck coefficient in the temperature range 300-1000 K, consistent with a resonant doping scheme. In contrast, Nb and Ta act as normal n-type dopants, as evident by the systematic decrease in electrical resistivity and Seebeck coefficient. The combination of enhanced Seebeck coefficient due to the presence of V resonant states and the reduced thermal conductivity has led to a state-of-the-art ZT of 1.3 near 850 K in n-type (Hf0.6Zr0.4)0.99V0.01NiSn0.995Sb0.005 alloys.

cond-mat.mtrl-sci↗
arXiv2017

Multigrid Methods for A Mixed Finite Element Method of The Darcy-Forchheimer Model

An efficient nonlinear multigrid method for a mixed finite element method of the Darcy-Forchheimer model is constructed in this paper. A Peaceman-Rachford type iteration is used as a smoother to decouple the nonlinearity from the divergence constraint. The nonlinear equation can be solved element-wise with a closed formulae. The linear saddle point system for the constraint is reduced into a symmetric positive definite system of Poisson type. Furthermore an empirical choice of the parameter used in the splitting is proposed and the resulting multigrid method is robust to the so-called Forchheimer number which controls the strength of the nonlinearity. By comparing the number of iterations and CPU time of different solvers in several numerical experiments, our multigrid method is shown to convergent with a rate independent of the mesh size and the Forchheimer number and with a nearly linear computational cost.

math.NA↗
arXiv2017

SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning

Visual attention has been successfully applied in structural prediction tasks such as visual captioning and question answering. Existing visual attention models are generally spatial, i.e., the attention is modeled as spatial probabilities that re-weight the last conv-layer feature map of a CNN encoding an input image. However, we argue that such spatial attention does not necessarily conform to the attention mechanism --- a dynamic feature extractor that combines contextual fixations over time, as CNN features are naturally spatial, channel-wise and multi-layer. In this paper, we introduce a novel convolutional neural network dubbed SCA-CNN that incorporates Spatial and Channel-wise Attentions in a CNN. In the task of image captioning, SCA-CNN dynamically modulates the sentence generation context in multi-layer feature maps, encoding where (i.e., attentive spatial locations at multiple layers) and what (i.e., attentive channels) the visual attention is. We evaluate the proposed SCA-CNN architecture on three benchmark image captioning datasets: Flickr8K, Flickr30K, and MSCOCO. It is consistently observed that SCA-CNN significantly outperforms state-of-the-art visual attention-based image captioning methods.

cs.CV↗
arXiv2017

Planecell: Representing the 3D Space with Planes

Reconstruction based on the stereo camera has received considerable attention recently, but two particular challenges still remain. The first concerns the need to aggregate similar pixels in an effective approach, and the second is to maintain as much of the available information as possible while ensuring sufficient accuracy. To overcome these issues, we propose a new 3D representation method, namely, planecell, that extracts planarity from the depth-assisted image segmentation and then projects these depth planes into the 3D world. An energy function formulated from Conditional Random Field that generalizes the planar relationships is maximized to merge coplanar segments. We evaluate our method with a variety of reconstruction baselines on both KITTI and Middlebury datasets, and the results indicate the superiorities compared to other 3D space representation methods in accuracy, memory requirements and further applications.

cs.CV↗
arXiv2017

Augmented Reality for Depth Cues in Monocular Minimally Invasive Surgery

One of the major challenges in Minimally Invasive Surgery (MIS) such as laparoscopy is the lack of depth perception. In recent years, laparoscopic scene tracking and surface reconstruction has been a focus of investigation to provide rich additional information to aid the surgical process and compensate for the depth perception issue. However, robust 3D surface reconstruction and augmented reality with depth perception on the reconstructed scene are yet to be reported. This paper presents our work in this area. First, we adopt a state-of-the-art visual simultaneous localization and mapping (SLAM) framework - ORB-SLAM - and extend the algorithm for use in MIS scenes for reliable endoscopic camera tracking and salient point mapping. We then develop a robust global 3D surface reconstruction frame- work based on the sparse point clouds extracted from the SLAM framework. Our approach is to combine an outlier removal filter within a Moving Least Squares smoothing algorithm and then employ Poisson surface reconstruction to obtain smooth surfaces from the unstructured sparse point cloud. Our proposed method has been quantitatively evaluated compared with ground-truth camera trajectories and the organ model surface we used to render the synthetic simulation videos. In vivo laparoscopic videos used in the tests have demonstrated the robustness and accuracy of our proposed framework on both camera tracking and surface reconstruction, illustrating the potential of our algorithm for depth augmentation and depth-corrected augmented reality in MIS with monocular endoscopes.

cs.CV↗
arXiv2016

The forward-backward asymmetry for massive bottom quarks at the $Z$ peak at next-to-next-to-leading order QCD

We compute the order $α_s^2$ QCD corrections to the $b$-quark forward-backward asymmetry in $e^+e^-\to b{\bar b}$ collisions at the $Z$ boson resonance, taking the non-zero mass of the $b$ quark into account. We determine these corrections with respect to both the $b$-quark axis and the thrust axis definition of the asymmetry. We compute also the distributions of these axes with respect to the electron beam. If one neglects the flavor singlet contributions to the $b$-quark asymmetry, as was done in previous computations for massless $b$ quarks, then the second-order QCD corrections for $m_b\neq 0$ are smaller in magnitude than the corresponding corrections for $m_b=0$. Including the singlet contributions slightly increases the magnitude of the corrections. The massive $α_s^2$ corrections to the $b$-quark forward-backward asymmetry slightly diminish the well-known tension between the bare $b$-quark asymmetry and the standard model fit from $2.9σ$ to $2.6σ$.

hep-ph↗
arXiv2016

Stabilized mixed finite element methods for linear elasticity on simplicial grids in $\mathbb{R}^{n}$

In this paper, we design two classes of stabilized mixed finite element methods for linear elasticity on simplicial grids. In the first class of elements, we use $\boldsymbol{H}(\mathbf{div}, Ω; \mathbb{S})$-$P_k$ and $\boldsymbol{L}^2(Ω; \mathbb{R}^n)$-$P_{k-1}$ to approximate the stress and displacement spaces, respectively, for $1\leq k\leq n$, and employ a stabilization technique in terms of the jump of the discrete displacement over the faces of the triangulation under consideration; in the second class of elements, we use $\boldsymbol{H}_0^1(Ω; \mathbb{R}^n)$-$P_{k}$ to approximate the displacement space for $1\leq k\leq n$, and adopt the stabilization technique suggested by Brezzi, Fortin, and Marini. We establish the discrete inf-sup conditions, and consequently present the a priori error analysis for them. The main ingredient for the analysis is two special interpolation operators, which can be constructed using a crucial $\boldsymbol{H}(\mathbf{div})$ bubble function space of polynomials on each element. The feature of these methods is the low number of global degrees of freedom in the lowest order case. We present some numerical results to demonstrate the theoretical estimates.

math.NA↗
arXiv2016

Top-quark pair production at next-to-next-to-leading order QCD in electron positron collisions

We set up a formalism, within the antenna subtraction framework, for computing the production of a massive quark-antiquark pair in electron positron collisions at next-to-next-to-leading order in the coupling $α_s$ of quantum chromodynamics at the differential level. Our formalism applies to the calculation of any infrared-safe observable. We apply this set-up to the production of top-quark top antiquark pairs in the continuum. We compute the production cross section and several distributions. We determine, in particular, the top-quark forward-backward asymmetry at order $α_s^2$. Our result agrees with previous computations of this observable.

hep-ph↗
arXiv2016

Inflationary spectra from a near $Ω$-deformed space-time transition point in Loop Quantum Cosmology

Anomaly-free perturbations of loop quantum cosmology with holonomy corrections reveal an $Ω$ -deformed spacetime structure, $Ω:=1-2ρ/ρ_c$, where $Ω<0$ indicates a Euclidean-like space and $Ω>0$ indicates a Lorentz-like space. It would be reasonable to give the initial value at the spacetime transition point, $ρ=ρ_c/2$, but we find that it is impossible to define a Minkowski-like vacuum even for large $k$ modes at that time. However, if we loosen the condition and give the initial value slightly after $Ω=0$, e.g., $Ω\simeq 0.2$, the vacuum state can be well defined and, furthermore the slow roll approximation also works well in that region. Both scalar and tensor spectra are considered in the framework of loop quantum cosmology with holonomy corrections. We find that if the energy density is not too small in relation to $ρ_c/2$ when the considered $k$ mode crossing the horizon, effective theory can give a much smaller scalar power spectrum than classical theory and the spectrum of tensor perturbations could blueshift. But when compared to other observations, since the energy densities when the modes crossed the horizon were significantly smaller than $ρ_c$,the results we get agree with previous work in the literature and with the classical inflation theory.

gr-qc↗
arXiv2016

Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study

It is well known that clothing fashion is a distinctive and often habitual trend in the style in which a person dresses. Clothing fashions are usually expressed with visual stimuli such as style, color, and texture. However, it is not clear which visual stimulus places higher/lower influence on the updating of clothing fashion. In this study, computer vision and machine learning techniques are employed to analyze the influence of different visual stimuli on clothing-fashion updates. Specifically, a classification-based model is proposed to quantify the influence of different visual stimuli, in which each visual stimulus's influence is quantified by its corresponding accuracy in fashion classification. Experimental results demonstrate that, on clothing-fashion updates, the style holds a higher influence than the color, and the color holds a higher influence than the texture.

cs.CV↗
arXiv2016

Fast Auxiliary Space Preconditioner for Linear Elasticity in Mixed Form

A block diagonal preconditioner with the minimal residual method and a block triangular preconditioner with the generalized minimal residual method are developed for Hu-Zhang mixed finite element methods of linear elasticity. They are based on a new stability result of the saddle point system in mesh-dependent norms. The mesh-dependent norm for the stress corresponds to the mass matrix which is easy to invert while the displacement it is spectral equivalent to Schur complement. A fast auxiliary space preconditioner based on the $H^1$ conforming linear element of the linear elasticity problem is then designed for solving the Schur complement. For both diagonal and triangular preconditioners, it is proved that the conditioning numbers of the preconditioned systems are bounded above by a constant independent of both the crucial Lamé constant and the mesh-size. Numerical examples are presented to support theoretical results. As byproducts, a new stabilized low order mixed finite element method is proposed and analyzed and superconvergence results of Hu-Zhang element are obtained.

math.NA↗
arXiv2016

Improved effective vector boson approximation revisited

We reexamine the improved effective vector boson approximation which is based on two-vector-boson luminosities $\mathrm{\mathbf{L}}_{\rm pol}$ for the computation of weak gauge-boson hard scattering subprocesses $V_1 V_2\to {\cal W}$ in high-energy hadron-hadron or $e^-e^+$ collisions. We calculate these luminosities for the nine combinations of the transverse and longitudinal polarizations of $V_1$ and $V_2$ in the unitary and axial gauge. For these two gauge choices the quality of this approach is investigated for the reactions $e^-e^+ \to W^- W^+ ν_e {\barν}_e$ and $e^-e^+ \to t {\bar t} ν_e {\barν}_e$ using appropriate phase-space cuts.

hep-ph↗
arXiv2016

Fast multilevel solvers for a class of discrete fourth order parabolic problems

In this paper, we study fast iterative solvers for the solution of fourth order parabolic equations discretized by mixed finite element methods. We propose to use consistent mass matrix in the discretization and use lumped mass matrix to construct efficient preconditioners. We provide eigenvalue analysis for the preconditioned system and estimate the convergence rate of the preconditioned GMRes method. Furthermore, we show that these preconditioners only need to be solved inexactly by optimal multigrid algorithms. Our numerical examples indicate that the proposed preconditioners are very efficient and robust with respect to both discretization parameters and diffusion coefficients. We also investigate the performance of multigrid algorithms with either collective smoothers or distributive smoothers when solving the preconditioner systems.

math.NA↗
arXiv2016

Multigrid Methods for Constrained Minimization Problems and Application to Saddle Point Problems

The first order condition of the constrained minimization problem leads to a saddle point problem. A multigrid method using a multiplicative Schwarz smoother for saddle point problems can thus be interpreted as a successive subspace optimization method based on a multilevel decomposition of the constraint space. Convergence theory is developed for successive subspace optimization methods based on two assumptions on the space decomposition: stable decomposition and strengthened Cauchy-Schwarz inequality, and successfully applied to the saddle point systems arising from mixed finite element methods for Poisson and Stokes equations. Uniform convergence is obtained without the full regularity assumption of the underlying partial differential equations. As a byproduct, a V-cycle multigrid method for non-conforming finite elements is developed and proved to be uniform convergent with even one smoothing step.

math.NA↗
arXiv2016

MultiGrid Preconditioners for Mixed Finite Element Methods of Vector Laplacian

Due to the indefiniteness and poor spectral properties, the discretized linear algebraic system of the vector Laplacian by mixed finite element methods is hard to solve. A block diagonal preconditioner has been developed and shown to be an effective preconditioner by Arnold, Falk, and Winther [Acta Numerica, 15:1--155, 2006]. The purpose of this paper is to propose alternative and effective block diagonal and block triangular preconditioners for solving this saddle point system. A variable V-cycle multigrid method with the standard point-wise Gauss-Seidel smoother is proved to be a good preconditioner for a discrete vector Laplacian operator. This multigrid solver will be further used to build preconditioners for the saddle point systems of the vector Laplacian and the Maxwell equations with divergent free constraint. The major benefit of our approach is that the point-wise Gauss-Seidel smoother is more algebraic and can be easily implemented as a black-box smoother.

math.NA↗