Open Access. Powered by Scholars. Published by Universities.®

Computer-Aided Engineering and Design Commons

Open Access. Powered by Scholars. Published by Universities.®

1,116 Full-Text Articles 2,136 Authors 605,986 Downloads 83 Institutions

All Articles in Computer-Aided Engineering and Design

Faceted Search

1,116 full-text articles. Page 6 of 49.

3d Floor Plan Recovery From Overlapping Spherical Images, Giovanni Pintore, Fabio Ganovelli, Ruggero Pintus, Roberto Scopigno, Enrico Gobbetti 2020 CRS4, Visual Computing Group, Cagliari, Italy.

3d Floor Plan Recovery From Overlapping Spherical Images, Giovanni Pintore, Fabio Ganovelli, Ruggero Pintus, Roberto Scopigno, Enrico Gobbetti

Computational Visual Media

We present a novel approach to automati-cally recover, from a small set of partially overlapping spherical images, an indoor structure representation in terms of a 3D floor plan registered with a set of 3D environment maps. We introduce several improvements over previous approaches based on color and spatial reasoning exploiting Manhattan world priors. Inparticular, we introduce a new method for geometric context extraction based on a 3D facet representation, which combines color distribution analysis of individual images with sparse multi-view clues. We also introduce an efficient method to combine the facets from different viewpoints in a single consistent model, taking ...


Resolving Display Shape Dependence Issues On Tabletops, James McNaughton, Tom Crick, Shamus Smith 2020 School of Education, Durham University, Durham DH1 3LE, UK.

Resolving Display Shape Dependence Issues On Tabletops, James Mcnaughton, Tom Crick, Shamus Smith

Computational Visual Media

Advances in display technologies are trans-forming the capabilities—and potential applications—of system interfaces. Previously, the overwhelming majority of systems have utilised rectangular displays; this may soon change with digital devices increasingly designed to be ubiquitous and pervasive, to facilitate frictionless human interaction. At present, software is invariably designed assuming it will be used with a display of a specific shape; however, there is an emerging demand for systems built around interacting with tabletop interfaces to be capable of handling a wide range of potential display shapes. In this paper, the design of software for use on a range of ...


Flic: Fast Linear Iterative Clustering With Active Search, Jiaxing Zhao, Ren Bo, Qibin Hou, Ming-Ming Cheng, Paul Rosin 2020 Nankai University, Tianjin 300350, China.

Flic: Fast Linear Iterative Clustering With Active Search, Jiaxing Zhao, Ren Bo, Qibin Hou, Ming-Ming Cheng, Paul Rosin

Computational Visual Media

In this paper, we reconsider the clustering problem for image over-segmentation from a new per-spective. We propose a novel search algorithm called "active search" which explicitly considers neighbor continuity. Based on this search method, we design a back-and-forth traversal strategy and a joint assignment and update step to speed up the algorithm. Compared to earlier methods, such as simple linear iterative clustering (SLIC) and its variants, which use fixed search regions and perform the assignment and the update steps separately, our novel scheme reduces the number of iterations required for convergence, and also provides better boundaries in the over-segmentation results ...


Acquiring Non-Parametric Scattering Phase Function From A Single Image, Yuki Minetomo, Hiroyuki Kubo, Takuya Funatomi, Mikio Shinya, Yasuhiro Mukaigawa 2020 Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192, Japan.

Acquiring Non-Parametric Scattering Phase Function From A Single Image, Yuki Minetomo, Hiroyuki Kubo, Takuya Funatomi, Mikio Shinya, Yasuhiro Mukaigawa

Computational Visual Media

Acquiring accurate scattering properties is important for rendering translucent materials. In particular, the phase function, which determines the distribution of scattering directions, plays a significant role in the appearance of a material. We propose a distinctive scattering theory that approximates the effect of single scattering to acquire the non-parametric phase function from a single image. Furthermore, in various experiments, we measured the phase functions from several real diluted media and rendered images of these materials to evaluate the effectiveness of our theory.


Fusionmls: Highly Dynamic 3d Reconstruction With Consumer-Grade Rgb-D Cameras, Siim Meerits, Diego Thomas, Vincent Nozick, Hideo Saito 2020 Department of Information and Computer Science,Keio University, Yokohama, Japan.

Fusionmls: Highly Dynamic 3d Reconstruction With Consumer-Grade Rgb-D Cameras, Siim Meerits, Diego Thomas, Vincent Nozick, Hideo Saito

Computational Visual Media

Multi-view dynamic three-dimensional reconstruction has typically required the use of custom shutter-synchronized camera rigs in order to capture scenes containing rapid movements or complex topology changes. In this paper, we demonstrate that multiple unsynchronized low-cost RGB-D cameras can be used for the same purpose. To alleviate issues caused by unsynchronized shutters, we propose a novel depth frame interpolation technique that allows synchronized data capture from highly dynamic 3D scenes. To manage the resulting huge number of input depth images, we also introduce an efficient moving least squares-based volumetric reconstruction method that generates triangle meshes of the scene. Our approach does ...


Component Spd Matrices: A Low-Dimensional Discriminative Data Descriptor For Image Set Classification, Kai-Xuan Chen, Xiao-Jun Wu 2020 School of IoT Engineering, Jiangnan University, Wuxi 214122,China. Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence, Jiangnan University, Wuxi 214122, China.

Component Spd Matrices: A Low-Dimensional Discriminative Data Descriptor For Image Set Classification, Kai-Xuan Chen, Xiao-Jun Wu

Computational Visual Media

In pattern recognition, the task of image set classification has often been performed by representing data using symmetric positive definite (SPD) matrices, in conjunction with the metric of the resulting Riemannian manifold. In this paper, we propose a new data representation framework for image sets which we call component symmetric positive definite representation (CSPD). Firstly, we obtain sub-image sets by dividing the images in the set into square blocks of the same size, and use a traditional SPD model to describe them. Then, we use the Riemannian kernel to determine similarities of corresponding sub-image sets. Finally, the CSPD matrix appears ...


Gpu Based Techniques For Deep Image Merging, Jesse Archer, Geoff Leach, Ron van Schyndel 2020 School of Science, RMIT University, Melbourne, 3000, Australia.

Gpu Based Techniques For Deep Image Merging, Jesse Archer, Geoff Leach, Ron Van Schyndel

Computational Visual Media

Deep images store multiple fragments per-pixel, each of which includes colour and depth, unlike traditional 2D flat images which store only a single colour value and possibly a depth value. Recently, deep images have found use in an increasing number of applications, including ones using transparency and compositing. A step in compositing deep images requires merging per-pixel fragment lists in depth order; little work has so far been presented on fast approaches.This paper explores GPU based merging of deep images using different memory layouts for fragment lists: linked lists, linearised arrays, and interleaved arrays. We also report performance improvements ...


Spatially Adaptive Long-Term Semi-Lagrangian Method For Accurate Velocity Advection, Takahiro Sato, Christopher Batty, Takeo Igarashi, Ryoichi Ando 2020 The University of Tokyo, Tokyo, Japan.

Spatially Adaptive Long-Term Semi-Lagrangian Method For Accurate Velocity Advection, Takahiro Sato, Christopher Batty, Takeo Igarashi, Ryoichi Ando

Computational Visual Media

We introduce a new advection scheme for fluid animation. Our main contribution is the use of long-term temporal changes in pressure to extend the commonly used semi-Lagrangian scheme further back along the time axis. Our algorithm starts by tracing sample points along a trajectory following the velocity field backwards in time for many steps. During this backtracing process, the pressure gradient along the path is integrated to correct the velocity of the current time step. We show that our method effectively suppresses numerical diffusion, retains small-scale vorticity, and provides better long-term kinetic energy preservation.


Traffic Signal Detection And Classification In Street Views Using An Attention Model, Yifan Lu, Jiaming Lu, Songhai Zhang, Peter Hall 2020 TNList, Tsinghua University, Beijing 100084, China.

Traffic Signal Detection And Classification In Street Views Using An Attention Model, Yifan Lu, Jiaming Lu, Songhai Zhang, Peter Hall

Computational Visual Media

Abstract Detecting small objects is a challenging task. We focus on a special case: the detection and classification of traffic signals in street views. We present a novel framework that utilizes a visual attention model to make detection more efficient, without loss of accuracy, and which generalizes. The attention model is designed to generate a small set of candidate regions at a suitable scale so that small targets can be better located and classified. In order to evaluate our method in the context of traffic signal detection, we have built a traffic light benchmark with over 15,000 traffic light ...


Dance To The Beat: Synchronizing Motion To Audio, Rachele Bellini, Yanir Kleiman, Daniel Cohen-Or 2020 Tel Aviv University, Tel Aviv 6997801, Israel.

Dance To The Beat: Synchronizing Motion To Audio, Rachele Bellini, Yanir Kleiman, Daniel Cohen-Or

Computational Visual Media

In this paper we introduce a video post-processing method that enhances the rhythm of a dancing performance, in the sense that the dancing movements are more in time to the beat of the music. The dancing performance as observed in a video is analyzed and segmented into motion intervals delimited by motion beats. We present an image-space method to extract the motion beats of a video by detecting frames at which there is a significant change in direction or motion stops. The motion beats are then synchronized with the music beats such that as many beats as possible are matched ...


Instantaneous Foveated Preview For Progressive Monte Carlo Rendering, Matias K. Koskela, Kalle V. Immonen, Timo T. Viitanen, Pekka O. Jääskeläinen, Joonas I. Multanen, Jarmo H. Takala 2020 Tampere University of Technology, Tampere, 33720, Finland.

Instantaneous Foveated Preview For Progressive Monte Carlo Rendering, Matias K. Koskela, Kalle V. Immonen, Timo T. Viitanen, Pekka O. Jääskeläinen, Joonas I. Multanen, Jarmo H. Takala

Computational Visual Media

Progressive rendering, for example Monte Carlo rendering of 360∘ content for virtual reality headsets, is a time-consuming task. If the 3D artist notices an error while previewing the rendering, they must return to editing mode, make the required changes, and restart rendering. We propose the use of eye-tracking-based optimization to significantly speed up previewing of the artist’s points of interest. The speed of the preview is further improved by sampling with a distribution that closely follows the experimentally measured visual acuity of the human eye, unlike the piecewise linear models used in previous work. In a comprehensive user study ...


Learning Adaptive Receptive Fields For Deep Image Parsing Networks, Zhen Wei, Yao Sun, Junyu Lin, Si Liu 2020 State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China. University of Chinese Academy of Sciences, Beijing 101408, China.

Learning Adaptive Receptive Fields For Deep Image Parsing Networks, Zhen Wei, Yao Sun, Junyu Lin, Si Liu

Computational Visual Media

In this paper, we introduce a novel approach to automatically regulate receptive fields in deep image parsing networks. Unlike previous work which placed much importance on obtaining better receptive fields using manually selected dilated convolutional kernels, our approach uses two affine transformation layers in the network’s backbone and operates on feature maps. Feature maps are inflated or shrunk by the new layer, thereby changing the receptive fields in the following layers. By use of end-to-end training, the whole framework is data-driven, without laborious manual intervention. The proposed method is generic across datasets and different tasks. We have conducted extensive ...


Relief Generation From 3d Scenes Guided By Geometric Texture Richness, Yongwei Miao, Yuliang Sun, Xudong Fang, Jiazhou Chen, Xudong Zhang, Renato Pajarola 2020 College of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China.

Relief Generation From 3d Scenes Guided By Geometric Texture Richness, Yongwei Miao, Yuliang Sun, Xudong Fang, Jiazhou Chen, Xudong Zhang, Renato Pajarola

Computational Visual Media

Typically, relief generation from an input 3D scene is limited to either bas-relief or high-relief modeling. This paper presents a novel unified scheme for synthesizing reliefs guided by the geometric texture richness of 3D scenes; it can generate both bas- and high-reliefs. The type of relief and compression coefficient can be specified according to the user’s artistic needs. We use an energy minimization function to obtain the surface reliefs, which contains a geometry preservation term and an edge constraint term. An edge relief measure determined by geometric texture richness and edge z-depth is utilized to achieve a balance between ...


Knowledge Graph Construction With Structure And Parameter Learning For Indoor Scene Design, Yuan Liang, Fei Xu, Song-Hai Zhang, Yu-Kun Lai, Taijiang Mu 2020 TNList, Department of Computer Science, Tsinghua University, Beijing 100084, China.

Knowledge Graph Construction With Structure And Parameter Learning For Indoor Scene Design, Yuan Liang, Fei Xu, Song-Hai Zhang, Yu-Kun Lai, Taijiang Mu

Computational Visual Media

We consider the problem of learning a representation of both spatial relations and dependencies between objects for indoor scene design. We propose a novel knowledge graph framework based on the entity-relation model for representation of facts in indoor scene design, and further develop a weakly-supervised algorithm for extracting the knowledge graph representation from a small dataset using both structure and parameter learning. The proposed framework is flexible, transferable, and readable. We present a variety of computer-aided indoor scene design applications using this representation, to show the usefulness and robustness of the proposed framework.


Diffusion Curves With Diffusion Coefficients, Hongwei Lin, Jingning Zhang, Chenkai Xu 2020 School of Mathematical Science, Zhejiang University, Hangzhou 310027, China. State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou 310058, China.

Diffusion Curves With Diffusion Coefficients, Hongwei Lin, Jingning Zhang, Chenkai Xu

Computational Visual Media

Diffusion curves can be used to generate vector graphics images with smooth variation by solving Poisson equations. However, using the classical diffusion curve model, it is difficult to ensure that the generated diffusion image satisfies desired constraints. In this paper, we develop a model for producing a diffusion image by solving a diffusion equation with diffusion coefficients, in which color layers and coefficient layers are introduced to facilitate the generation of the diffusion image. Doing so allows us to impose various constraints on the diffusion image, such as diffusion strength, diffusion direction, diffusion points, etc., in a unified computational framework ...


Magic Sheets: Visual Cryptography With Common Shares, Naoki Kita, Kazunori Miyata 2020 Japan Advanced Institute of Science and Technology, Nomi, 923-1292, Japan.

Magic Sheets: Visual Cryptography With Common Shares, Naoki Kita, Kazunori Miyata

Computational Visual Media

Visual cryptography (VC) is an encryption technique for hiding a secret image in distributed and shared images (referred to as shares). VC schemes are employed to encrypt multiple images as meaningless, noisy patterns or meaningful images. However, decrypting multiple secret images using a unique share is difficult with traditional VC. We propose an approach to hide multiple images in meaningful shares. We can decrypt multiple images simultaneously using a common share, which we refer to as a magic sheet. The magic sheet decrypts multiple secret images depending on a given share. The shares are printed on transparencies, and decryption is ...


Surface Remeshing With Robust User-Guided Segmentation, Dawar Khan, Dong-Ming Yan, Fan Ding, Yixin Zhuang, Xiaopeng Zhang 2020 National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. University of Chinese Academy of Sciences, Beijing, 100049, China.

Surface Remeshing With Robust User-Guided Segmentation, Dawar Khan, Dong-Ming Yan, Fan Ding, Yixin Zhuang, Xiaopeng Zhang

Computational Visual Media

Surface remeshing is widely required in modeling, animation, simulation, and many other computer graphics applications. Improving the elements’ quality is a challenging task in surface remeshing. Existing methods often fail to efficiently remove poor-quality elements especially in regions with sharp features. In this paper, we propose and use a robust segmentation method followed by remeshing the segmented mesh. Mesh segmentation is initiated using an existing Live-wire interaction approach and is further refined using local mesh operations. The refined segmented mesh is finally sent to the remeshing pipeline, in which each mesh segment is remeshed independently. An experimental study compares our ...


Automatic Texture Exemplar Extraction Based On Global And Local Textureness Measures, Huisi Wu, Xiaomeng Lyu, Zhenkun Wen 2020 Shenzhen University, Shenzhen 518000, China.

Automatic Texture Exemplar Extraction Based On Global And Local Textureness Measures, Huisi Wu, Xiaomeng Lyu, Zhenkun Wen

Computational Visual Media

Texture synthesis is widely used for modeling the appearance of virtual objects. However, traditional texture synthesis techniques emphasize creation of optimal target textures, and pay insufficient attention to choice of suitable input texture exemplars. Currently, obtaining texture exemplars from natural images is a labor intensive task for the artists, requiring careful photography and significant post-processing. In this paper, we present an automatic texture exemplar extraction method based on global and local textureness measures. To improve the efficiency of dominant texture identification, we first perform Poisson disk sampling to randomly and uniformly crop patches from a natural image. For global textureness ...


Ez-Manipulator: Designing A Mobile, Fast, And Ambiguity-Free 3d Manipulation Interface Using Smartphones, Po-Huan Tseng, Shih-Hsuan Hung, Pei-Ying Chiang, Chih-Yuan Yao, Hung-Kuo Chu 2020 “National Tsing Hua University”, Hsinchu 30013, Taiwan,China.

Ez-Manipulator: Designing A Mobile, Fast, And Ambiguity-Free 3d Manipulation Interface Using Smartphones, Po-Huan Tseng, Shih-Hsuan Hung, Pei-Ying Chiang, Chih-Yuan Yao, Hung-Kuo Chu

Computational Visual Media

Interacting with digital contents in 3D is an essential task in various applications such as modeling packages, gaming, virtual reality, etc. Traditional interfaces using keyboard and mouse or trackball usually require a non-trivial amount of working space as well as a learning process. We present the design of EZ-Manipulator, a new 3D manipulation interface using smartphones that supports mobile, fast, and ambiguity-free interaction with 3D objects. Our system leverages the built-in multi-touch input and gyroscope sensor of smartphones to achieve 9 degrees-of-freedom axis-constrained manipulation and free-form rotation. Using EZ-Manipulator to manipulate objects in 3D is easy. The user merely has ...


Transhist: Occlusion-Robust Shape Detection In Cluttered Images, Chu Han, Xueting Liu, Lok Tsun Sinn, Tien-Tsin Wong 2020 The Chinese University of Hong Kong, Hong Kong, China.

Transhist: Occlusion-Robust Shape Detection In Cluttered Images, Chu Han, Xueting Liu, Lok Tsun Sinn, Tien-Tsin Wong

Computational Visual Media

Shape matching plays an important role in various computer vision and graphics applications such as shape retrieval, object detection, image editing, image retrieval, etc. However, detecting shapes in cluttered images is still quite challenging due to the incomplete edges and changing perspective. In this paper, we propose a novel approach that can efficiently identify a queried shape in a cluttered image. The core idea is to acquire the transformation from the queried shape to the cluttered image by summarising all point-to-point transformations between the queried shape and the image. To do so, we adopt a point-based shape descriptor, the pyramid ...


Digital Commons powered by bepress