Mutual information maximizing GAN inversion for real face with identity preservation

Recent generative adversarial networks (GANs) have yielded remarkable performance in face image synthesis. GAN inversion embeds an image into the latent space of a pretrained generator, enabling it to be used for real face manipulation. However, current inversion approaches for real faces suffer the dilemma of initialization collapse and identity loss. In this paper, we propose a hierarchical GAN inversion for real faces with identity preservation based on mutual information maximization. We first use a facial domain guaranteed initialization to avoid the initialization collapse. Furthermore, we prove that maximizing the mutual information between inverted faces and their identities is equivalent to minimizing the distance between identity features from inverted and original faces. Optimization for real face inversion with identity preservation is implemented on this mutual information-maximizing constraint. Extensive experimental results show that our approach outperforms state-of-the-art solutions for inverting and editing real faces, particularly in terms of face identity preservation.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

从Pentawards奖看扁平化视觉元素在包装设计中的应用

探讨扁平化视觉元素在包装设计中的运用方法及影响,丰富食品包装应用设计的创作理念和风格样式。以Pentawards获奖作品为研究对象,综合分析图形、文字、色彩和版面等核心视觉要素呈现的扁平化特征与原则。结果表明,扁平化视觉元素在包装设计中的运用方法:图形简洁矢量化、颜色稚拙块状化、文字扁平模块化、版面简约秩序化,产生了品牌形象个性化、信息传达效率高、多媒体适用性强等影响,验证了扁平化设计理念在包装设计的可行性与有效性。     

基于边缘和局部熵融合的视觉安全性评估方法

针对基于局部熵进行加密图像视觉安全性评估存在块效应的局限性，引入图像的边缘特征，通过共有边缘来衡量加密图像与原始图像的边缘相似度，消除了块效应。由于局部熵对加密等级低的图像不敏感，边缘相似度对加密等级高的图像不敏感，将两个评估方法进行自适应融合，提出[SLEES]（Local Entropy and Edge Similarity，[SLEES]）指标。通过改变图像像素位置和图像像素值的加密方式处理图像和视频帧进行测试，实验结果表明，[SLEES]指标相比传统评估指标有更好的鲁棒性，评估范围更广。     

基于机器视觉的机车齿轮毂全自动双轴拧紧机的设计和应用

设计了基于机器视觉的机车齿轮毂全自动双轴拧紧机,根据拧紧工艺和扭矩控制原理实现对螺栓拧紧力矩的控制;通过丝杠变径机构,实现不同规格齿轮毂螺栓拧紧;利用机器视觉实现螺栓位置的识别以及初始位置的确定;讨论了自动拧紧机控制系统的硬件组成和软件系统配置,并介绍了防错、防漏功能的设计流程。螺栓自动拧紧机可提高装配精度和操作效率,降低工人的劳动强度。     

儿童用品TBT通报数据可视化预警研究

探索采用数据可视化技术分析儿童用品TBT通报数据,以可视化图形图像呈现通报热点并揭示趋势信息,提出对策与建议,助力为儿童用品产业升级、TBT预警数据分析和信息传播工作提供新思路,提高中小企业的国外市场准入机会。     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

基于区块链应用模式的铁路旅客身份认证系统

采用“区块链技术+不对称加密+生物识别+身份认证”应用模式，依托智能手机客户端设计与开发一套铁路旅客身份认证系统.基于Ethereum开发平台，应用truffle开发框架，实现铁路旅客身份认证系统智能合约的编写与部署.系统针对传统铁路身份认证模式的不足，将旅客身份数据分布式存储，弱化中心化服务器的压力，提升旅客身份数据的安全性和鲁棒性；进行生物信息认证确保旅客对身份信息的所有权；利用非对称加密技术在保护旅客隐私、实现实名制的前提下增强数据的透明性.基于区块链应用模式的铁路旅客身份认证系统能够让用户身份实现本地存储、信息摘要链上校验，实现铁路旅客身份信息数据访问的细粒度控制，保障铁路旅客身份信息安全，提升铁路旅客的乘车体验.     

深圳抽水蓄能电站监控新技术应用研究与实践

通过对安防、工业电视和门禁等新技术的研究,设计了一套先进的监控系统,包括硬件平台、系统管理、应用软件,利用深圳抽水蓄能电站已形成的光纤网络通道把分布在方圆10 km范围内多个站端设备以环路的方式连接起来,把可靠成熟的新技术融合到整个平台。自首台机组成功投运,监控系统为电站正常运行保驾护航,高清摄像机、视觉识别、行为分析、边界防护等新技术的应用为工程项目增添了亮点,使电站现场管理更加智能化、规范化。