Mechanical Engineering Commons^™

Light Field Salient Object Detection: A Review And Benchmark, Keren Fu, Yao Jiang, Ge-Peng Ji, Tao Zhou, Qijun Zhao, Deng-Ping Fan

Computational Visual Media

Salient object detection (SOD) is a long-standing research topic in computer vision with increasing interest in the past decade. Since light fields record comprehensive information of natural scenes that benefit SOD in a number of ways, using light field inputs to improve saliency detection over conventional RGB inputs is an emerging trend. This paper provides the first comprehensive review and a benchmark for light field SOD, which has long been lacking in the saliency community. Firstly, we introduce light fields, including theory and data forms, and then review existing studies on light field SOD, covering ten traditional models, seven deep ...

Recent Advances In Glinty Appearance Rendering, Junqiu Zhu, Sizhe Zhao, Yanning Xu, Xiangxu Meng, Lu Wang, Ling-Qi Yan

Computational Visual Media

The interaction between light and materials is key to physically-based realistic rendering. However, it is also complex to analyze, especially when the materials contain a large number of details and thus exhibit "glinty" visual effects. Recent methods of producing glinty appearance are expected to be important in next-generation computer graphics. We provide here a comprehensive survey on recent glinty appearance rendering. We start with a definition of glinty appearance based on microfacet theory, and then summarize research works in terms of representation and practical rendering. We have implemented typical methods using our unified platform and compare them in terms of ...

Automatic Location And Semantic Labeling Of Landmarks On 3d Human Body Models, Shan Luo, Qitong Zhang, Jieqing Feng

Computational Visual Media

Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design. The diversity of pose and shape of human body models and the semantic gap make landmarking a challenging problem. Inthis paper, a learning-based method is proposed to locate landmarks on human body models by analyzing the relationship between geometric descriptors and semantic labels of landmarks. A shape alignmentalgorithm is proposed to align human body models to break symmetric ambiguity. A symmetry-awaredescriptor is proposed based on the structure of the human body models, which is robust to both pose and shape variations in ...

Constructing Self-Supporting Surfaces With Planar Quadrilateral Elements, Long Ma, Sidan Yao, Jianmin Zheng, Yang Liu, Yuanfeng Zhou, Shi-Qing Xin, Ying He

Computational Visual Media

We present a simple yet effective method for constructing 3D self-supporting surfaces with planar quadrilateral (PQ) elements. Starting with a triangular discretization of a self-supporting surface, we firstcompute the principal curvatures and directions of each triangular face using a new discrete differential geometryapproach, yielding more accurate results than existing methods. Then, we smooth the principal direction field to reduce the number of singularities. Next, we partition all faces into two groups in terms of principalcurvature difference. For each face with small curvature difference, we compute a stretch matrix that turns the principal directions into a pair of conjugate directions. For ...

Blnet: Bidirectional Learning Network For Point Clouds, Wenkai Han, Hai Wu, Chenglu Wen, Cheng Wang, Xin Li

Computational Visual Media

The key challenge in processing point clouds lies in the inherent lack of ordering and irregularity of the 3D points. By relying on per-point multi-layer perceptions (MLPs), most existing point-based approaches only address the first issue yet ignore the second one. Directly convolving kernels with irregular points will result in loss of shape information. This paper introduces a novel point-based bidirectional learning network (BLNet) to analyze irregular 3D points. BLNet optimizes the learning of 3D points through two iterative operations: feature-guided point shifting and feature learning from shifted points, so as to minimise intra-class variances, leading to a more regular ...

Joint Self-Supervised And Reference-Guided Learning For Depth Inpainting, Heng Wu, Kui Fu, Yifan Zhao, Haokun Song, Jia Li

Computational Visual Media

Depth information can benefit various computer vision tasks on both images and videos. However, depth maps may suffer from invalid values in many pixels, and also large holes. To improve such data, we propose a joint self-supervised and reference-guided learning approach for depth inpainting. For the self-supervised learning strategy, we introduce an improved spatial convolutional sparse coding module in which total variation regularization is employed to enhance the structural information while preserving edge information. This module alternately learns a convolutional dictionary and sparse coding from a corrupted depth map. Then, both the learned convolutional dictionary and sparse coding are convolved ...

Image-Guided Color Mapping For Categorical Data Visualization, Qian Zheng, Min Lu, Sicong Wu, Ruizhen Hu, Joel Lanir, Hui Huang

Computational Visual Media

Appropriate color mapping for categorical data visualization can significantly facilitate the discovery of underlying data patterns and effectively bring out visual aesthetics. Some systems suggest pre-defined palettes for this task. However, a predefined color mapping is not always optimal, failing to consider users’ needs for customization. Given an input cate-gorical data visualization and a reference image, we present an effective method to automatically generate a coloring that resembles the reference while allowing classes to be easily distinguished. We extract a color palette with high perceptual distance between the colors by sampling dominant and discriminable colors from the image’s color ...

Self-Supervised Coarse-To-Fine Monocular Depth Estimation Using A Lightweight Attention Module, Yuanzhen Li, Fei Luo, Chunxia Xiao

Computational Visual Media

Self-supervised monocular depth estimation has been widely investigated and applied in previous works. However, existing methods suffer from texture-copy, depth drift, and incomplete structure. It is difficult for normal CNN networks to completely understand the relationship between the object and its surrounding environment. Moreover, it is hard to design the depth smoothness loss to balance depth smoothness and sharpness. To address these issues, we propose a coarse-to-fine method with a normalized convolutional block attention module (NCBAM). In the coarse estimation stage, we incorporate the NCBAM into depth and pose networks to overcome the texture-copy and depth drift problems. Then, we ...

High Fidelity Virtual Try-On Network Via Semantic Adaptation And Distributed Componentization, Chenghu Du, Feng Yu, Minghua Jiang, Ailing Hua, Yaxin Zhao, Xiong Wei, Tao Peng, Xinrong Hu

Computational Visual Media

Image-based virtual try-on systems have significant commercial value in online garment shopping. However, prior methods fail to appropriately handle details, so are defective in maintaining the original appearance of organizational items including arms, the neck, and in-shop garments. We propose a novel high fidelity virtual try-on network to generate realistic results. Specifically, a distributed pipeline is used for simultaneous generation of organizational items. First, the in-shop garment is warped using thin plate splines (TPS) to give a coarse shape reference, and then a corresponding target semantic map is generated, which can adaptively respond to the distribution of different items triggered ...

Uav Rapidly-Deployable Stage Sensor With Electro-Permanent Magnet Docking Mechanism For Flood Monitoring In Undersampled Watersheds, Corinne A, Smith, Joud Satme, Jacob Martin, Austin Downey, Nikolaos Vitzilaios, Jasim Imran

Faculty Publications

The availability of historical flood data is vital in recognizing weather-related trends and outlining necessary precautions for at-risk communities. Flood frequency, magnitude, endurance, and volume are traditionally recorded using established streamgages; however, the material and installation costs allow only a few streamgages in a region, which yield a narrow data selection. In particular, stage, the vertical water height in a water body, is an important parameter in determining flood trends. This work investigates a low-cost, compact, rapidly-deployable alternative to traditional stage sensors that will allow for denser sampling within a watershed and a more detailed record of flood events. The ...

A Cfd-Based Scaling Analysis On Liquid And Paint Droplets Moving Through A Weak Concurrent Airflow Stream, Masoud Arabghahestani, Nelson Akafuah, Tianxiang Li, Kozo Saito

Progress in Scale Modeling, an International Journal

We conducted volume of fluids (VOF) multiphase model numerical simulations to obtain the interaction among all the major governing forces identified in our previous paper. Our numerical experiments are intended to assess the droplet generation process and the jetting behavior by providing specific input conditions, offering CFD as a tool to study scaling correlations instead of physical experiments. Water droplets that can represent waterborne paints were generated by piezo-generated sinusoidal waveforms at the inlet of the nozzle. The governing forces included the external piezo-based wave-generation force, the inertial force of droplets, the inertial force of air, the viscose force of ...

Predicting Stochastic Lightning Mechanical Damage Effects On Carbon Fiber Reinforced Polymer Matrix Composites, Juhyeong Lee, Syed Zulfiqar Hussain Shah

Mechanical and Aerospace Engineering Faculty Publications

Three stochastic air blast models are developed with spatially varying elastic properties and failure strengths for predicting lightning mechanical damage to AS4/3506 carbon/epoxy composites subjected to < 100 kA peak currents: (1) the conventional weapon effects program (CWP) model, (2) the coupled eulerianlagrangian (CEL) model, and (3) the smoothed-particle hydrodynamics (SPH) model. This work is an extension of our previous studies [1–4] that used deterministic air blast models for lightning mechanical damage prediction. Stochastic variations in composite material properties were generated using the Box-Muller transformation algorithm with the mean (i.e., room temperature experimental data) and their standard deviations (i.e., 10% of the mean herein as reference). The predicted dynamic responses and corresponding damage initiation prediction for composites under equivalent air blast loading were comparable for the deterministic and stochastic models. Overall, the domains with displacement, von-Mises stress, and damage initiation contours predicted in the stochastic models were somewhat sporadic and asymmetric along the fiber’s local orientation and varied intermittently. This suggests the significance of local property variations in lightning mechanical damage prediction. Thus, stochastic air blast models may provide a more accurate lightning mechanical damage approximation than traditional (deterministic) air blast models. All stochastic models proposed in this work demonstrated satisfactory accuracy compared to the baseline models, but required substantial computational time due to the random material model generation/assignment process, which needs to be optimized in future work.

Design Of Composite Double-Slab Radar Absorbing Structures Using Forward, Inverse, And Tandem Neural Networks, Devin Nielsen, Juhyeong Lee, Young-Woo Nam

Mechanical and Aerospace Engineering Faculty Publications

The survivability and mission of a military aircraft is often designed with minimum radar cross section (RCS) to ensure its long-term operation and maintainability. To reduce aircraft’s RCS, a specially formulated Radar Absorbing Structures (RAS) is primarily applied to its external skins. A Ni-coated glass/epoxy composite is a recent RAS material system designed for decreasing the RCS for the X-band (8.2 – 12.4 GHz), while maintaining efficient and reliable structural performance to function as the skin of an aircraft. Experimentally measured and computationally predicted radar responses (i.e., return loss responses in specific frequency ranges) of multi-layered ...

Hyper-Velocity Impact Performance Of Foldcore Sandwich Composites, Nathan Hoch, Chase Mortensen, Juhyeong Lee, Khari Harrison, Kalyan Raj Kota, Thomas Lacy

Mechanical and Aerospace Engineering Faculty Publications

A foldcore is a novel core made from a flat sheet of any material folded into a desired pattern. A foldcore sandwich composite (FSC) provides highly tailorable structural performance over conventional sandwich composites made with honeycomb or synthetic polymer foam cores. Foldcore design can be optimized to accommodate complex shapes and unit cell geometries suitable for protective shielding structures

This work aims to characterize hypervelocity impact (> 2000 m/s, HVI) response and corresponding damage morphologies of carbon fiber reinforced polymer (CFRP) FSCs. A series of normal (0° impact angle) and oblique (45° impact angle) HVI (~3km/s nominal projectile velocity ...

Atherogenic Potential Of Microgravity Hemodynamics In The Carotid Bifurcation: A Numerical Investigation, Philippe Sucosky, Varun Vinayak Kalaiarasan, Graham B. Quasebarth, Patricia Strack, Jason A. Shar

Faculty Subvention Fund

Long-duration spaceflight poses multiple hazards to human health, including physiological changes associated with microgravity. The hemodynamic adaptations occurring upon entry into weightlessness have been associated with retrograde stagnant flow conditions and thromboembolic events in the venous vasculature but the impact of microgravity on cerebral arterial hemodynamics and function remains poorly understood. The objective of this study was to quantify the effects of microgravity on hemodynamics and wall shear stress (WSS) characteristics in 16 carotid bifurcation geometries reconstructed from ultrasonography images using computational fluid dynamics modeling. Microgravity resulted in a significant 21% increase in flow stasis index, a 22–23% decrease ...

Technoeconomic Analysis Of Changing Pv Array Convective Cooling Through Changing Array Spacing, Matthew Prilliman, Sarah E. Smith, Brooke Stanislawski, Janine M.F. Keith, Timothy J. Silverman, Marc Calaf, Raul Bayoan Cal

Mechanical and Materials Engineering Faculty Publications and Presentations

Accuracy in photovoltaic (PV) module temperature modeling is crucial to achieving precision in energy performance yield calculations and subsequent economic evaluations of PV projects. While there have been numerous approaches to PV temperature modeling based on both the steady-state and transient thermal assumptions, there have been few attempts to account for changing convective cooling on PV module surfaces resulting from changes in the PV system layout. Changes in system row spacing, in particular, can have a meaningful impact on module electrical efficiency and subsequent economic performance, even when considering additional costs from the changes in row spacing. Using a heat ...

Tailored Surface Textures To Increase Friction—A Review, Henara L. Costa, Jörg Schille, Andreas Rosenkranz

Friction

Surface textures with micro-scale feature dimensions still hold great potential to enhance the frictional performance of tribological systems. Apart from the ability of surface texturing to reduce friction, surface textures can also be used to intentionally increase friction in various applications that rely on friction for their adequate functioning. Therefore, this review aims at presenting the state-of-the-art regarding textured surfaces for high-friction purposes. After a brief general introduction, the recent trends and future paths in laser surface texturing are summarized. Then, the potential of surface textures to increase friction in different applications including adhesion, movement transmission and control, biomimetic applications ...

Role Of Nanoparticles In Achieving Macroscale Superlubricity Of Graphene/Nano-Sio2 Particle Composites, Panpan Li, Li Ji, Hongxuan Li, Lei Chen, Xiaohong Liu, Huidi Zhou, Jianmin Chen

Friction

Recent studies have reported that adding nanoparticles to graphene enables macroscale superlubricity to be achieved. This study focuses on the role of nanoparticles in achieving superlubricity. First, because graphene nanoscrolls can be formed with nanoparticles as seeds under shear force, the applied load (or shear force) is adjusted to manipulate the formation of graphene nanoscrolls and to reveal the relationship between graphene-nanoscroll formation and superlubricating performance. Second, the load-carrying role of spherical nano-SiO₂ particles during the friction process is verified by comparison with an elaborately designed fullerene that possesses a hollow-structured graphene nanoscroll. Results indicate that the incorporated nano-SiO ...

Optimization Of Pore Structure And Wet Tribological Properties Of Paper-Based Friction Materials Using Chemical Foaming Technology, Chang Li, Jie Fei, Enzhi Zhou, Rui Lu, Xiaohang Cai, Yewei Fu, Hejun Li

Friction

Paper-based friction materials are porous materials that exhibit anisotropy; they exhibit random pore sizes and quantities during their preparation, thereby rendering the control of their pore structure difficult. Composites with different pore structures are obtained by introducing chemical foaming technology during their preparation to regulate their pore structure and investigate the effect of pore structure on the properties of paper-based friction materials. The results indicate that the skeleton density, total pore area, average pore diameter, and porosity of the materials increase after chemical foaming treatment, showing a more open pore structure. The addition of an organic chemical foaming agent improves ...

Numerical Study On Butterfly Wings Around Inclusion Based On Damage Evolution And Semi-Analytical Method, Ye Zhou, Caichao Zhu, Xiaojin Chen, Wei Ye

Friction

Butterfly wings are closely related to the premature failure of rolling element bearings. In this study, butterfly formation is investigated using the developed semi-analytical three-dimensional (3D) contact model incorporating inclusion and material property degradation. The 3D elastic field introduced by inhomogeneous inclusion is solved by using numerical approaches, which include the equivalent inclusion method (EIM) and the conjugate gradient method (CGM). The accumulation of fatigue damage surrounding inclusions is described using continuum damage mechanics. The coupling between the development of the damaged zone and the stress field is considered. The effects of the inclusion properties on the contact status and ...