Interactive level-of-detail selection using image-based quality metric for large volume visualization

For large volume visualization, an image-based quality metric is difficult to incorporate for level-of-detail selection and rendering without sacrificing the interactivity. This is because it is usually time-consuming to update view-dependent information as well as to adjust to transfer function changes. In this paper, we introduce an image-based level-of-detail selection algorithm for interactive visualization of large volumetric data. The design of our quality metric is based on an efficient way to evaluate the contribution of multiresolution data blocks to the final image. To ensure real-time update of the quality metric and interactive level-of-detail decisions, we propose a summary table scheme in response to runtime transfer function changes and a GPU-based solution for visibility estimation. Experimental results on large scientific and medical data sets demonstrate the effectiveness and efficiency of our algorithm     

Efficient visualization of 3D models on hardware-limited portable devices

Managing the geometry of a 3D scene efficiently is a key aspect of an interactive 3D application. This aspect is more important if we target at portable devices, which have limited hardware capabilities. Developing new means for improving the interaction with 3D content in mobile devices is key. The aim of this work is to present a technique which can manage the level-of-detail of 3D meshes in portable devices. This solution has been devised considering the restrictions that this kind of devices poses. The results section shows how the integration has been successful while obtaining good performance.     

一种基于卡通画的线条画提取方法

给出了一种从卡通画中提取线条画的新方法。方法由三部分组成:线条提取、线条绘制和风格变换。给出了基于形态学方法细化图像,把结果中离散像素点深度优先遍历生成笔划路径集合,用不同细节来控制线条绘制,达到不同程度的抽象效果。给出了生成具有夸张风格的线条画的方法,实验结果显示用文中方法能从图像中抽象出生动的线条画。     

基于区域分解的并行动态LOD构建算法

面向大规模可视数据的高速绘制问题,提出了一种基于区域分解的并行动态LOD（level-of-detail,层次细节模型）构建算法。算法首先改进了传统的渐进网格方法,实现了基于二次误差测度网格简化算法的渐进网格方法;接着提出了一种基于模型包围盒的区域分解算法,实现了原始模型的自适应区域分解;在每个子区域上,并行地执行渐进网格方法,实现了模型的并行动态LOD构建。实验结果表明,该算法可生成高质量的LOD模型,具备理想的加速比和可扩放性;与串行算法相比,该算法有效地提高了算法的执行效率。     

Real-time animation of complex hairstyles

True real-time animation of complex hairstyles on animated characters is the goal of this work, and the challenge is to build a mechanical model of the hairstyle which is sufficiently fast for real-time performance while preserving the particular behavior of the hair medium and maintaining sufficient versatility for simulating any kind of complex hairstyles. Rather than building a complex mechanical model directly related to the structure of the hair strands, we take advantage of a volume free-form deformation scheme. We detail the construction of an efficient lattice mechanical deformation model which represents the volume behavior of the hair strands. The lattice is deformed as a particle system using state-of-the-art numerical methods, and animates the hairs using quadratic B-spline interpolation. The hairstyle reacts to the body skin through collisions with a metaball-based approximation. The model is highly scalable and allows hairstyles of any complexity to be simulated in any rendering context with the appropriate trade off between accuracy and computation speed, fitting the need of level-of-detail optimization schemes.     

FPGA implementation of semi-fragile reversible watermarking by histogram bin shifting in real time

In this paper, field programmable gate array (FPGA) implementation of reversible watermarking (RW) algorithm by histogram bin shifting (HBS) that can be used for real-time applications of medical and military images has been presented. As the tolerance level of distortion has to be minimal, RW scheme is necessary here. The reversible mode of the process helps in extracting both the original image and the watermark at the receiver end after undergoing through embedding and decoding procedure. The embedded watermark contains the underlying security information of the host images in case of any infringement. Although software implementations of RW schemes are available, very few attempts have been made for hardware realizations of such schemes. The inherent delay associated with software implementations can be minimized by using an on-chip hardware that performs the watermarking process immediately after capturing the image in real time. In this paper, the embedding and decoding procedures involved in the watermarking scheme are implemented using Xilinx System Generator and carries out a detailed design and analysis of the hardware architectures required for the embedding and extraction processes. The device utilization results for both the embedding and decoding process is low and practically viable. The maximum operating frequency for embedding and extraction processes are 445.330 and 201.824 MHz, respectively, which shows improved performance results over similar existing research work in the literature. The power consumptions for embedding and extraction processes are found to be 1.215 and 0.104 W, respectively. To the best of our knowledge, this is the first FPGA-based hardware implementation of RW by HBS.     

Graphic object feature extraction system based on Cuckoo Search Algorithm

Multimedia systems often use various detection methods to track relevant objects in images and video frames. The tracking scheme is often based on capturing of significant points in the object, which are used by implemented methods to extract the shape, dimensions, etc. and then further process these information. In recent years many advances in Computational Intelligence methods and approaches have been reported. Therefore the question has arisen if these, i.e. heuristics, are applicable to multimedia tracking systems?This article is to discuss developed heuristic methods for Key-Points tracking and shape extraction. In the following sections of this work developed approaches, in particular a dedicated Cuckoo Search Algorithm and Firefly Algorithm versions, are presented and discussed in comparison to some classical methods to show potential advantages and disadvantages. Benchmark tests and experimental research results are presented to show efficacy and extraction precision on test images.     

Structure-based brushes: a mechanism for navigating hierarchicallyorganized data and information spaces

Interactive selection is a critical component in exploratory visualization, allowing users to isolate subsets of the displayed information for highlighting, deleting, analysis, or focused investigation. Brushing, a popular method for implementing the selection process, has traditionally been performed in either screen space or data space. In this paper, we introduce an alternate, and potentially powerful, mode of selection that we term structure-based brushing, for selection in data sets with natural or imposed structure. Our initial implementation has focused on hierarchically structured data, specifically very large multivariate data sets structured via hierarchical clustering and partitioning algorithms. The structure-based brush allows users to navigate hierarchies by specifying focal extents and level-of-detail on a visual representation of the structure. Proximity-based coloring, which maps similar colors to data that are closely related within the structure, helps convey both structural relationships and anomalies. We describe the design and implementation of our structure-based brushing tool. We also validate its usefulness using two distinct hierarchical visualization techniques, namely hierarchical parallel coordinates and tree-maps. Finally, we discuss relationships between different classes of brushes and identify methods by which structure-based brushing could be extended to alternate data structures     

Automatic transformation from TIDES to TimeML annotation

Until recently, most systems performing temporal extraction and reasoning from text have focused on recognizing and normalizing temporal expressions alone, for which the TIDES annotation scheme has been adopted. Temporal awareness of a text, however, involves not only identifying the temporal expressions, but the events which these expressions anchor, as well as other events which must be ordered relative to them. Because of these broader concerns, TimeML has been developed as an annotation specification that encompasses not only temporal expressions, but all temporally relevant aspects of a text. The annotation schemes, however, are not interchangeable, resulting in incompatible corpora and accompanying extraction algorithms for each standard. In this paper, we describe an automatic migration process from the TIMEX2 tags of TIDES to the TIMEX3 tags of TimeML. This transformation procedure has been implemented and evaluated with two different corpora, obtaining 93.3 and 89.2% overall F-Measure respectively.     

Efficient high-quality volume rendering of SPH data

High quality volume rendering of SPH data requires a complex order-dependent resampling of particle quantities along the view rays. In this paper we present an efficient approach to perform this task using a novel view-space discretization of the simulation domain. Our method draws upon recent work on GPU-based particle voxelization for the efficient resampling of particles into uniform grids. We propose a new technique that leverages a perspective grid to adaptively discretize the view-volume, giving rise to a continuous level-of-detail sampling structure and reducing memory requirements compared to a uniform grid. In combination with a level-of-detail representation of the particle set, the perspective grid allows effectively reducing the amount of primitives to be processed at run-time. We demonstrate the quality and performance of our method for the rendering of fluid and gas dynamics SPH simulations consisting of many millions of particles.     

Level-of-detail for cognitive real-time characters

We present a solution for the real-time simulation of artificial environments containing cognitive and hierarchically organized agents at constant rendering framerates. We introduce a level-of-detail concept to behavioral modeling, where agents populating the world can be both reactive and proactive. The disposable time per rendered frame for behavioral simulation is variable and determines the complexity of the presented behavior. A special scheduling algorithm distributes this time to the agents depending on their level-of-detail such that visible and nearby agents get more time than invisible or distant agents. This allows for smooth transitions between reactive and proactive behavior. The time available per agent influences the proactive behavior, which becomes more sophisticated because it can spend time anticipating future situations. Additionally, we exploit the use of hierarchies within groups of agents that allow for different levels of control. We show that our approach is well-suited for simulating environments with up to several hundred agents with reasonable response times and the behavior adapts to the current viewpoint.     

Facial feature localization based on an improved active shape model

The original active shape model (ASM) has already been applied to the areas such as image segmentation, feature points localization, and contour extraction. However, the original ASM suffers from the loss of accuracy and low speed in real time applications. Due to this, a new scheme of active shape model for facial feature extraction is proposed in this paper. In this scheme, the improvement of the performance of the original ASM concerns the following three aspects. Firstly, the profile of the original ASM is extended from 1D to 2D. Secondly, each profile related to different features are constructed separately. Thirdly, the length of the profile varies with different levels. The simulations are carried out using the SJTU dataset, which contains 2273 face images. Experimental results demonstrate that the proposed scheme exhibits better performance than the original ASM.     

A unified subdivision approach for multi-dimensional non-manifold modeling

This paper presents a new unified subdivision scheme that is defined over a k-simplicial complex in n-D space with k≤3. We first present a series of definitions to facilitate topological inquiries during the subdivision process. The scheme is derived from the double (k+1)-directional box splines over k-simplicial domains. Thus, it guarantees a certain level of smoothness in the limit on a regular mesh. The subdivision rules are modified by spatial averaging to guarantee C¹ smoothness near extraordinary cases. Within a single framework, we combine the subdivision rules that can produce 1-, 2-, and 3-manifolds in arbitrary n-D space. Possible solutions for non-manifold regions between the manifolds with different dimensions are suggested as a form of selective subdivision rules according to user preference. We briefly describe the subdivision matrix analysis to ensure a reasonable smoothness across extraordinary topologies, and empirical results support our assumption. In addition, through modifications, we show that the scheme can easily represent objects with singularities, such as cusps, creases, or corners. We further develop local adaptive refinement rules that can achieve level-of-detail control for hierarchical modeling. Our implementation is based on the topological properties of a simplicial domain. Therefore, it is flexible and extendable. We also develop a solid modeling system founded on our subdivision schemes to show potential benefits of our work in industrial design, geometric processing, and other applications.     

Seamless patches for GPU-based terrain rendering

In this paper we present a novel approach for interactive rendering of large terrain datasets. Our approach is based on subdividing a terrain into rectangular patches at different resolutions. Each patch is represented by four triangular tiles that are selected form different resolutions, and four strips which are used to stitch the four tiles in a seamless manner. Such a scheme maintains resolution changes within patches through the stitching strips, and not across patches. At runtime, these patches are used to construct a level-of-detail representation of the input terrain based on view-parameters. A selected level of detail only includes the layout of the patches and their boundary edges resolutions. The layout includes the location and dimension of each patch. Within the graphics hardware, the GPU generates the meshes of the patches by using scaled instances of cached tiles and assigns elevation for each vertex from cached textures. Since adjacent rectangular patches agree on the resolution of the common edges, the resulted mesh does not include cracks or degenerate triangles. Our algorithm manages to achieve quality images at high frame rates while providing seamless transition between different levels of detail.     

Toward multi-programmed workloads with different memory footprints: a self-adaptive last level cache scheduling scheme

With the emerging of 3D-stacking technology, the dynamic random-access memory (DRAM) can be stacked on chips to architect the DRAM last level cache (LLC). Compared with static randomaccess memory (SRAM), DRAM is larger but slower. In the existing research papers, a lot of work has been devoted to improving the workload performance using SRAM and stacked DRAM together, ranging from SRAM structure improvement, to optimizing cache tag and data access. Instead, little attention has been paid to designing an LLC scheduling scheme for multi-programmed workloads with different memory footprints. Motivated by this, we propose a self-adaptive LLC scheduling scheme, which allows us to utilize SRAM and 3D-stacked DRAM efficiently, achieving better workload performance. This scheduling scheme employs (1) an evaluation unit, which is used to probe and evaluate the cache information during the process of programs being executed; and (2) an implementation unit, which is used to self-adaptively choose SRAM or DRAM. To make the scheduling scheme work correctly, we develop a data migration policy. We conduct extensive experiments to evaluate the performance of our proposed scheme. Experimental results show that our method can improve the multi-programmed workload performance by up to 30% compared with the state-of-the-art methods.     

An Integrated Face Rec gniti n System Based n Multiscale L cal Discriminatory Features

Despite some successes, the process of Automatic Facial Recognition (AFR) remains a significant challenge when unconstrained imaging conditions are involved. The authors believe that this occurs because an effective feature extraction method of facial images has not been found so far. In this paper a new approach to extract powerful local discriminatory features is described. First, the wavelet transform is used for extraction of multi-resolution coarse features, and then the emphasis is placed on the extraction of Multiscale fine Local Discriminatory Features (MLDFs). Instead of using traditional wavelet features, the authors examine the multiscale local statistical characteristics to derive stronger discriminatory features based on some important wavelet subbands. To efficiently utilise potentials of the extracted multi-MLDFs, an integrated recognition system is developed where the multi-classifiers first conduct the corresponding coarse classification, then a decision making scheme is used to associate different priorities with each of the classifiers to make the final recognition. Experiments have shown that this scheme provides superior performance to popular methods, such as Principal Components Analysis (PCA or Eigenface), wavelet features, neural networks, etc.     

A robust control scheme for nonlinear non-isothermal uncertain jacketed continuous stirred tank reactor

A Non-isothermal Jacketed Continuous Stirred Tank Reactor (CSTR) is extensively used in chemical as well as in other process industries to manufacture different products. The dynamics of non-isothermal CSTR are highly nonlinear and open-loop unstable in nature. Moreover, it may have parametric uncertainties, disturbances and un-modeled side reactions which may cause the reactor temperature to deviate from the reference value. This deviation may degrade quality of the product because the chemical reaction inside the CSTR depends on reactor temperature. For such a nonlinear, unstable and uncertain process, designing a control scheme with the ability to reject the effects of disturbances along with a good reference tracking capability is a challenging control engineering problem. In this work, a novel robust sliding mode control technique named as Improved Integral Sliding Mode Control (IISMC) has been presented for uncertain non-isothermal jacketed CSTR process. Moreover, a variety of recently developed sliding mode control techniques such as Classical Integral Sliding Mode Control (CISMC) and Super Twisted Algorithm based Sliding Mode Control (STA-SMC) have also been devised and compared with the proposed approach in order to investigate the effectiveness of the proposed scheme. A Lyapunov based analysis has also been provided to assure the robust stability of the closed loop process. Furthermore, in order to extend the state feedback approach to the output feedback scheme, two robust observers; High Gain Observer (HGO) and Extended High Gain Observer (EHGO), are also designed for the very process. They have also been compared with each other and have been investigated for robust stability using Lyapunov based approach. Finally, an output feedback control scheme using IISMC and EHGO has been presented and its performance has been examined and compared with the IISMC based state feedback approach. The simulation results show that the proposed control scheme effectively rejects the uncertainties and disturbances without leading the process to instability and offers good reference tracking capabilities.     

基于单水平集的多目标轮廓提取

多目标轮廓提取是图像分割的重要研究内容.文章在Chan和Vese的无边界主动轮廓模型(简称CV模型)的基础上,提出基于单水平集的多目标轮廓提取算法.CV模型只能实现单目标的轮廓提取,主要原因是不能使水平集函数驱动的轮廓线在某些目标区域正确分裂,没有有效利用轮廓线的拓扑分裂信息.通过修正CV模型,引入标记模板,用于追踪零水平集的分裂情况,对不同的准目标区域区别处理;引入图像区域均值模板,用于估计可能淹没在背景区域中的目标区域,促使水平集函数在上述目标区域充分变形,使对应零水平集充分分裂,实现多目标轮廓提取.并且文章提供了一系列不同条件下的实验结果,并与其它类似的研究成果进行比较,结果表明,该文的工作是有意义的.     

基于Trace变换的人脸特征提取技术研究*

为了提高人脸特征的稳定性和区分度,提出了一种基于Trace变换的人脸特征提取算法。算法通过几种不同的泛函函数对预处理后的人脸图像进行组合作用,得到该图像的一个Trace特征向量,从而建立了一种新的人脸特征表达方式。基于ORL人脸数据库的实验结果表明,该算法所提出的人脸特征对同一个人不同表情、不同光照条件下的图像变化能够保持较好的稳定性,同时对不同人的人脸图像具有较高的区分能力,在人脸识别的实际应用中是一种可行的方法。