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This paper involves the study of pull-in voltage of a Shape Memory Alloy (SMA) based cantilever beam. The study is carried out by applying electrostatic forces and varying the dimensions. Nitinol which is a SMA is used for the simulation to get required results. An electrostatic force generated by an applied voltage between the top movable micro-cantilever and fixed ground plane bends the micro-cantilever...
Field emission from “nano diodes” encounter strong deviations from the tunneling barrier presupposed in Fowler Nordheim theory. Modifications to the emission barrier are modeled using a hyperbolic geometry to find trajectories along which Gamow factor is found; a quadratic equivalent potential is determined, and a shape factor method is used to evaluate the total current from a protrusion or wedge...
While hand geometry trait has been widely used to perform biometric recognition, majority of the methods employ images acquired against a uniform background. If segmentation of the hand is implemented, existing techniques can be used in cluttered backgrounds as well. This paper presents an approach for accurate segmentation of human hands for images following the aforementioned conditions using skin...
We propose a novel, practical solution for high quality reconstruction of axially-symmetric transparent objects. While a special case, such transparent objects are ubiquitous in the real world. Common examples of these are glasses, goblets, tumblers, carafes, etc., that can have very unique and visually appealing forms making their reconstruction interesting for vision and graphics applications. Our...
Previous approaches for scene text detection have already achieved promising performances across various benchmarks. However, they usually fall short when dealing with challenging scenarios, even when equipped with deep neural network models, because the overall performance is determined by the interplay of multiple stages and components in the pipelines. In this work, we propose a simple yet powerful...
Generation of 3D data by deep neural network has been attracting increasing attention in the research community. The majority of extant works resort to regular representations such as volumetric grids or collection of images, however, these representations obscure the natural invariance of 3D shapes under geometric transformations, and also suffer from a number of other issues. In this paper we address...
While the ready availability of 3D scan data has influenced research throughout computer vision, less attention has focused on 4D data, that is 3D scans of moving non-rigid objects, captured over time. To be useful for vision research, such 4D scans need to be registered, or aligned, to a common topology. Consequently, extending mesh registration methods to 4D is important. Unfortunately, no ground-truth...
3D shape models are naturally parameterized using vertices and faces, i.e., composed of polygons forming a surface. However, current 3D learning paradigms for predictive and generative tasks using convolutional neural networks focus on a voxelized representation of the object. Lifting convolution operators from the traditional 2D to 3D results in high computational overhead with little additional...
This paper focuses on semantic scene completion, a task for producing a complete 3D voxel representation of volumetric occupancy and semantic labels for a scene from a single-view depth map observation. Previous work has considered scene completion and semantic labeling of depth maps separately. However, we observe that these two problems are tightly intertwined. To leverage the coupled nature of...
3D Reconstruction from shading information through Photometric Stereo is considered a very challenging problem in Computer Vision. Although this technique can potentially provide highly detailed shape recovery, its accuracy is critically dependent on a numerous set of factors among them the reliability of the light sources in emitting a constant amount of light. In this work, we propose a novel variational...
We introduce a data-driven approach to complete partial 3D shapes through a combination of volumetric deep neural networks and 3D shape synthesis. From a partially-scanned input shape, our method first infers a low-resolution – but complete – output. To this end, we introduce a 3D-Encoder-Predictor Network (3D-EPN) which is composed of 3D convolutional layers. The network is...
We consider the problem of sampling at unknown locations. We prove that, in this setting, if we take arbitrarily many samples of a polynomial or real bandlimited signal, it is possible to find another function in the same class, arbitrarily far away from the original, that could have generated the same samples. In other words, the error can be arbitrarily large. Motivated by this, we prove that, for...
Tangible learning is a promising branch, especially for scientific learning, allowing an enhanced sensorial involvement and participation by children. While a lot is being done on the side of programming, less has been investigated on elementary spatial and geometric concepts. The paper presents i-Vertex, an open-hardware framework for tangible serious games on geometry concepts for primary school...
We present an approach to analyse near-field effects on nanostructured gold films by finite element simulations. The studied samples are formed by fabricating gold films near the percolation threshold and then applying laser damage. Resulting samples have complicated structures, which then was captured using scanning transmission electron microscopy (STEM) and the obtained dark field images are used...
Building envelopes manage several crucial functions, including structural, thermal, hygric and aesthetic functions. Classic façade concepts usually work with static elements like glass, metal or composite panels that primarily provide protection against the elements, and an additional layer of active systems that manage dynamic tasks like light protection or thermal regulation. Kinematic shell elements...
For a team of unmanned aerial vehicles (UAVs) in the leader-follower type, the dynamic relative position relationships between followers and the leader are described with elastic distance vector. The desired geometric shape in formation change and maintenance is constructed via the elastic coefficient matrix of distance in the three dimensional space. In the second-order kinematics model, follower...
Facial analysis plays very important role in many vision applications, such as authentication and entertainments. The very early works in the 1990s mostly focus on estimating geometric deformations of facial landmarks to address this task. While in the past several years, more and more efforts have been made to directly learn an appearance regression for facial analysis. Though training regressions...
A major challenge in visual highway traffic analytics is to disaggregate individual vehicles from clusters formed in dense traffic conditions. Here we introduce a data driven 3D generative reasoning method to tackle this segmentation problem. The method is comprised of offline (learning) and online (inference) stages. In the offline stage, we fit a mixture model for the prior distribution of vehicle...
This study is focused on the impact of laser and scanner control parameters on the formation of laser polished (LPed) lines. The combined effect of a scanner control parameter called laser-on-delay (LOD) and varying laser power is analyzed with respect to the shape of the LPed line. The ideal shape of an LPed line is characterized by semicircular ends with a diameter equal to the width of the stable...
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