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Hierarchical Vectorization for facial images

Computational Visual Media 2024年第1期10卷 97-118页

作者： Qian Fu Linlin Liu Fei Hou Ying He School of Computer Science and Engineering Nanyang Technological University639798SingaporeSingapore Data61 Commonwealth Scientific and Industrial Research OrganisationSydney2015Australia Interdisciplinary Graduate School Nanyang Technological University and Alibaba Group639798SingaporeSingapore State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing100190China University of Chinese Academy of Sciences Beijing100049China

The explosive growth of social media means portrait editing and retouching are in high demand.While portraits are commonly captured and stored as raster images,editing raster images is non-trivial and requires the user to be highly skilled.Aiming at developing intuitive and easy-to-use portrait editing tools,we propose a novel Vectorization method that can automatically convert raster images into a 3-tier hierarchical representation.The base layer consists of a set of sparse diffusion curves(DCs)which characterize salient geometric features and low-frequency colors,providing a means for semantic color transfer and facial expression editing.The middle level encodes specular highlights and shadows as large,editable Poisson regions(PRs)and allows the user to directly adjust illumination by tuning the strength and changing the shapes of PRs.The top level contains two types of pixel-sized PRs for high-frequency residuals and fine details such as pimples and pigmentation.We train a deep generative model that can produce high-frequency residuals automatically.Thanks to the inherent meaning in vector primitives,editing portraits becomes easy and intuitive.In particular,our method supports color transfer,facial expression editing,highlight and shadow editing,and automatic retouching.To quantitatively evaluate the results,we extend the commonly used FLIP metric(which measures color and feature differences between two images)to consider illumination.The new metric,illumination-sensitive FLIP,can effectively capture salient changes in color transfer results,and is more consistent with human perception than FLIP and other quality measures for portrait images.We evaluate our method on the FFHQR dataset and show it to be effective for common portrait editing tasks,such as retouching,light editing,color transfer,and expression editing.

关键词： face editing Vectorization Poisson editing color transfer illumination editing expression editing

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Vectorization of line drawing image based on junction analysis

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Science China(Information Sciences) 2015年第7期58卷 99-112页

作者： CHEN JiaZhou LEI Qi MIAO YongWei PENG QunSheng College of Computer Science Zhejiang University of Technology State Key Laboratory of CAD&CG Zhejiang University

Converting a scanned or shot line drawing image into a vector graph can facilitate further edit and reuse, making it a hot research topic in computer animation and image processing. Besides avoiding noise influence, its main challenge is to preserve the topological structures of the original line drawings, such as line junctions, in the procedure of obtaining a smooth vector graph from a rough line drawing. In this paper, we propose a Vectorization method of line drawings based on junction analysis, which retains the original structure unlike done by existing methods. We first combine central line tracking and contour tracking, which allows us to detect the encounter of line junctions when tracing a single path. Then, a junction analysis approach based on intensity polar mapping is proposed to compute the number and orientations of junction branches.Finally, we make use of bending degrees of contour paths to compute the smoothness between adjacent branches,which allows us to obtain the topological structures corresponding to the respective ones in the input image.We also introduce a correction mechanism for line tracking based on a quadratic surface fitting, which avoids accumulating errors of traditional line tracking and improves the robustness for vectorizing rough line drawings.We demonstrate the validity of our method through comparisons with existing methods, and a large amount of experiments on both professional and amateurish line drawing images.

关键词： Vectorization line drawing line tracking junction analysis vector graph

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DBSC-Based Grayscale Line Image Vectorization

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Journal of Computer Science & Technology 2006年第2期21卷 244-248页

作者： Konstantin Melikhov 田丰邱杰陈泉谢福顺 Nanyang Technological University School of Computer Engineering Singapore

Vector graphics plays an important role in computer animation and imaging technologies. However present techniques and tools cannot fully replace traditional pencil and paper. Additionally, vector representation of an image is not always available. There is not yet a good solution for vectorizing a picture drawn on a paper. This work attempts to solve the problem of vectorizing grayscale line drawings. The solution proposed uses Disk B-Spline curves to represent strokes of an image in vector form. The algorithm builds a vector representation from a grayscale raster image, which can be a scanned picture for instance. The proposed method uses a Gaussian sliding window to calculate skeleton and perceptive width of a stroke. As a result of Vectorization, the given image is represented by a set of Disk B-Spline curves.

关键词： Vectorization skeletonization Disk B-Spline curves

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A Parallel Approach to Discords Discovery in Massive Time Series Data

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Computers, Materials & Continua 2021年第2期66卷 1867-1878页

作者： Mikhail Zymbler Alexander Grents Yana Kraeva Sachin Kumar Department of Computer Science South Ural State UniversityChelyabinsk454080Russian

A discord is a refinement of the concept of an anomalous subsequence of a time series.Being one of the topical issues of time series mining,discords discovery is applied in a wide range of real-world areas(medicine,astronomy,economics,climate modeling,predictive maintenance,energy consumption,etc.).In this article,we propose a novel parallel algorithm for discords discovery on high-performance cluster with nodes based on many-core accelerators in the case when time series cannot fit in the main memory.We assumed that the time series is partitioned across the cluster nodes and achieved parallelization among the cluster nodes as well as within a single node.Within a cluster node,the algorithm employs a set of matrix data structures to store and index the subsequences of a time series,and to provide an efficient Vectorization of computations on the accelerator.At each node,the algorithm processes its own partition and performs in two phases,namely candidate selection and discord refinement,with each phase requiring one linear scan through the partition.Then the local discords found are combined into the global candidate set and transmitted to each cluster node.Next,a node performs refinement of the global candidate set over its own partition resulting in the local true discord set.Finally,the global true discords set is constructed as intersection of the local true discord sets.The experimental evaluation on the real computer cluster with real and synthetic time series shows a high scalability of the proposed algorithm.

关键词： Time series discords discovery computer cluster many-core accelerator Vectorization

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A TensorFIow-based new high-performance computational framework for CFD

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Journal of Hydrodynamics 2020年第4期32卷 735-746页

作者： Xi-zeng Zhao Tian-yu Xu Zhou-teng Ye Wei-jie Liu Ocean College Zhejiang UniversityZhoushan 316021China The Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of EducationZhejiang UniversityZhoushan 316021China

In this study,a computational framework in the field of artificial intelligence was applied in computational fluid dynamics(CFD)field.This Framework,which was initially proposed by Google Al department,is called"TensorFlow".An improved CFD model based on this framework was developed with a high-order difference method,which is a constrained interpolation profile(CIP)scheme for the base flow solver of the advection term in the Navier-Stokes equations,and preconditioned conjugate gradient(PCG)method was implemented in the model to solve the Poisson equation.Some new features including the convolution,Vectorization,and graphics processing unit(GPU)acceleration were implemented to raise the computational efficiency.The model was tested with several benchmark cases and shows good performance.Compared with our former CIP-based model,the present Tensor Flow-based model also shows significantly higher computational efficiency in large-scale computation.The results indicate TensorFlow could be a promising framework for CFD models due to its ability in the computational acceleration and convenience for programming.

关键词： TensorFlow Vectorization Navier-Stokes equations graphics processing unit(GPU)acceleration constrained interpolation profile(CIP)method preconditioned conjugate gradient(PCG)method

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Real data extraction process and procedure of geophysical exploration profile

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Geodesy and Geodynamics 2020年第2期11卷 112-119页

作者： Jiapei Wang Guangliang Yang Chongyang Shen Hongbo Tan Guiju Wu Kai Sun Key Laboratory of Earthquake Geodesy Institute of SeismologyChina Earthquake AdministrationWuhan 430071China Institute of Geodesy and Geophysics Chinese Academy of SciencesWuhan 430077China University of Chinese Academy of Sciences Beijing 100049China

In this paper,we present an open python procedure with Jupyter notebook,for data extraction and Vectorization of geophysical explo ration profile.Constrained by observation routes and traffic conditions,geophysical exploration profiles tend to bend curved roads for easy observation,however,it must be projected onto a straight line when data processing and analyzing.After projection,we don’t know the true position of the obtained crustal structure.Nonetheless,when the results used as an initial constraint condition for other geophysical inversion,such as gravity inversion,we need to know the true position of the data rather than the distance to the starting point.We solved this problem by profile Vectorization and reprojection.The method can be used for extraction data of various geophysical exploration profiles,such as seismic reflection profiles,gravity profiles.

关键词： Data extraction Vectorization Profile Geophysical exploration Python

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Study on the Method to Measure the Evidence Simulation Degree

Study on the Method to Measure the Evidence Simulation Degre...

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第25届中国控制与决策会议

作者： LI Yongsen CAO Ze MIN Jie Management School Anhui University of Architecture

ISBN: (纸本)9781467355339

Some absurdities can be well dispelled or prevented if the simulation degree of different evidence bodies is defined properly and scientifically. This paper reconstructs and describes the frame of discernment by Euclid space. It presents a new method to measure the simulation degree of different evidence bodies based on vectorized evidence. The application of simulation degree to dispel the absurdities is also given in the paper.

关键词： Evidence theory Vectorization Simulation degree Support degree

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Raster to Vector Conversion for Engineering Drawings:Survey and Prospect

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Computer Aided Drafting,Design and Manufacturing 2006年第2期16卷 71-77页

作者： CHENG Bin ZHANG Shu-sheng SHI Yun-fei LEI Guang-ming The key Laboratory of Contemporary Design and Integrated Manufacturing Technology Ministry of Education Northwestern Polytechnical University Xi＇an 710072 China School of Science Xi＇an University of Architecture ＆ Technology Xi＇an 710055 China

Recent development and recognition methods of raster to vector conversion for engineering drawings are presented. The advantages and disadvantages of all existing models are analyzed. Some research challenges and futu... 详细信息

关键词： raster to vector conversion graphic recognition engineering drawings Vectorization

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Kernel Optimization on Short-Range Potentials Computations in Molecular Dynamics Simulations

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国际计算机前沿大会会议论文集 2015年第B12期 67-69页

作者： Xianmeng Wang Jianjiang Li Jue Wang Xinfu He Ningming Nie University of Science and Technology Beijing BeijingChina Supercomputing Center Computer Network Information CenterChinese Academy of ScienceBeijingChina China Institute of Atomic Energy BeijingChina

We present multi-threading and SIMD optimizations on short-range potential calculation kernel in Molecular Dynamics.For the multi-threading optimization,we design a partition-and-two-steps(PTS)method to avoid write conflicts caused by using Newton’s third law.Our method eliminates serialization bottle-neck without extra memory.We implement our PTS method using OpenMP.Afterwards,we discuss the influence of the cutoff if statement on the performance of Vectorization in MD simulations.We propose a pre-searching neighbors method,which makes about 70%atoms meet the cutoff check,reducing a large amount of redundant calculation.The experiment results prove our PTS method is scalable and efficient.In double precision,our 256-bit SIMD implementation is about 3×faster than the scalar version.

关键词： Molecular dynamics EAM SIMD Vectorization OpenMP Short-range potential High-performance computing

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Intelligent Approaches for Vectorizing Image Outlines

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Journal of Software Engineering and Applications 2012年第12期5卷 78-83页

作者： Muhammad Sarfraz Department of Information Science Kuwait University Adailiya Campus P.O. Box 5969 Safat 13060 Kuwait

Two computing approaches, based on linear and conic splines, are proposed here in reviewed and extended for vectorizing image outlines. Both of the approaches have various phases including extracting outlines of images, detecting corner points from the detected outlines, and curve fitting. Interpolation splines are the bases of the two approached. Linear spline approach is straight forward as it does not have a degree of freedom.in terms of some shape controller in its description. However, the idea of the soft computing approach, namely simulated annealing, has been utilized for conic splines. This idea has been incorporated to optimize the shape parameters in the description of the generalized conic spline. Both of the linear and conic approaches ultimately produce optimal results for the approximate Vectorization of the digital contours obtained from the generic shapes.

关键词： Imaging soft computing Vectorization corner points curve fitting

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