【往届均已检索】2022年视觉，图像与信号处理国际会议(ICVISP 2022)

2022年视觉，图像与信号处理国际会议(ICVISP 2022)欢迎计算机视觉、图像和信号处理领域的研究人员、开发人员和行业从业者参与到这个开放的论坛中来，分享该领域内的研究新发现、交流见解和经验教训等。在这个会议上，来自全球各地的领先研究人员和行业专家将通过口头报告等形式介绍该领域的最新研究。该平台的交流将进一步推进计算机视觉、图像和信号处理领域的发展。参与该会能有效帮助各位参会者结交该领域的研究人员并建立富有成效的合作。以更好地跟上该领域的持续发展与变化。

2022年视觉，图像与信号处理国际会议

2022 International Conference on Vision, Image and Signal Processing

(ICVISP 2022)

会议时间：2022.12.9-11

会议地点：马来西亚，吉隆坡

会议网址：www.icvisp.org

检索收录：EI Compendex、Scopus

重要时间节点

摘要投稿 2022年8月25日前

全文投稿 2022年9月5日前

Part Two 历史出版

ICVISP 2021 已发表至IEEE Computer Society's Conference Publishing Services (CPS), 并被IEEE Xplore、EI Compendex 及Scopus检索。会议论文集链接: 

https://ieeexplore.ieee.org/xpl/conhome/9700490/proceeding

ICVISP 2020 已发表至ACM Conference series, 并被EI Compendex 及Scopus检索。会议论文集链接: 

https://dl.acm.org/doi/proceedings/10.1145/3448823  

ICVISP 2019 已发表至ACM Conference series，并被EI Compendex 及Scopus.检索。会议论文集链接：

https://dl.acm.org/citation.cfm?id=3387168

ICVISP 2018 已发表至 ACM Conference series, 并被EI Compendex、Scopus检索。会议论文集链接：http://dl.acm.org/citation.cfm?id=3271553

ICVISP 2017已由Conference Publishing Services出版，被IEEE Xplore、EI Compendex和Scopus检索 。会议论文集链接：

https://ieeexplore.ieee.org/xpl/conhome/8121827/proceeding

Part  Three

会议举办地：广州

Part Four

 Keynote Speaker 

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李友福教授

香港城市大学机械工程系

李友福教授于1993年获得牛津大学工程科学系机器人学博士学位。1993年至1995年在英国阿伯里斯特威斯威尔士大学计算机科学系从事研究工作。1995年加入香港城市大学，现任机械工程学系教授。他的研究兴趣包括机器人感知、机器人视觉和视觉跟踪。在这些领域发表论文400余篇，其中SCI收录期刊论文180余篇。李博士在机器人传感与视觉领域获得多项奖项，包括IEEE Sensors Council的IEEE Sensors Journal最佳论文奖、教育部自然科学研究二等奖、湖北省自然科学研究一等奖、湖北省一等奖。浙江省自然科学研究二等奖。在斯坦福大学、2020 年和 Career Long 评选的世界上被引用次数最多的科学家中，他名列前 2%。他曾担任 IEEE Transactions on Automation Science and Engineering (T-ASE) 的副主编、IEEE Robotics and Automation Magazine (RAM) 的副主编和客座编辑。

演讲题目：Visual sensing and tracking for robotic applications

演讲摘要：Visual sensing and tracking are needed in many engineering applications including robotics. In this talk, I will present our research in visual sensing for automated 3D sensing in general and for motion tracking for robotics in particular. Different approaches in our investigation in 3D vision will be reported. These include an active vision approach to 3D visual sensing. For robotic applications, visual sensing in 3D is often needed, but the calibration remains tedious and inflexible with traditional approach. To this end, we have investigated the relevant issues for different visual sensing systems. A flexible calibration method desires the vision system parameters to be recalibrated automatically or with less operator interference whenever the configuration of the system is changed, but practically this is often hard to achieve. Various attempts were made in our previous works to enhance the flexibility in the visual sensing calibration. I will present some them including the work on omni-directional visual sensing and tracking. Another case to present is that of gaze tracking where the issues in the modeling and calibration are addressed with our new calibration method developed.

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Prof. Borko Furht

佛罗里达大西洋大学

Prof. Borko Furht是佛罗里达州博卡拉顿佛罗里达大西洋大学 (FAU) 电气工程和计算机科学系的教授。他还是 NSF 赞助的 FAU 高级知识支持产业/大学合作研究中心的主任。在加入 FAU 之前，他是德国戴姆勒奔驰计算机公司 Modcomp (Ft. Lauderdale) 的研究副总裁和开发高级总监，佛罗里达州科勒尔盖布尔斯的迈阿密大学教授和南斯拉夫Boris Kidric-Vinca 研究所的高级研究员。他目前的研究领域是多媒体系统、视频编码和压缩、3D 视频和图像系统、无线多媒体、医疗应用和云计算。他是《多媒体工具与应用杂志》(Springer) 的创始人和主编，最近与人共同创办了《大数据杂志》(Springer)。他获得了多项技术和出版奖项，并为许多高科技公司提供咨询服务，包括 IBM、惠普、施乐、通用电气、JPL、NASA、霍尼韦尔和 RCA。他在视频编码领域拥有 60 多项专利和专利申请。他曾多次受邀演讲、主题演讲、研讨会和教程。他曾担任多家高科技公司的董事会主席和董事，并担任 Cisco、Qualcomm、Adobe 和 Bell Canada 的专家证人。

演讲题目：Next Generation of Video Coding Technology: Standards, Patent war, Politics, and Financial Battle

演讲摘要：This keynote talk is about next generation of video coding standards including Versatile Video Coding (VVC) and Video Coding for Machines (VCM). The presenter’s team has been working on these two standards and produced more than 60 patents in the field, which were assigned to the Boston’s company OP Solutions. The talk will include technical innovations, which make, for example, the VVC standard about 50% more efficient in terms of compression ratio than the present HEVC standard for the same quality of video. There are a range of evolutionary technologies in VVC, including intra prediction, inter prediction, transformation, in loop filtering, palette coding, block partitioning, affine motion, and decoder side search, which will be presented in the talk. Besides technical innovations, we will also talk about the process of VVC and VCM standard development, and technical and political war besides the scene. Video coding standards and related patents provide a great generator of revenue. Only Netflix pays about $400 million royalty for using video coding standard for distributing its movies. In order to avoid paying such royalties Google developed VP9 open royalty-free video coding system mainly used on Google’s video platform YuTube. Several powerful companies, Google, Microsoft, Amazon, Cisco, and Netflix have developed open-source video compression technology AV1, which competes with VVC standard. In this talk we will discuss technical and political issues, video coding standards vs open systems.

We will also present the new video coding standard in making, Video Coding for Machines. VCM attempts to bridge the gap between feature coding for machine vision and video coding for human vision. In the talk we will discuss the basic VCM encoder and decoder architecture, and our patent applications how to implement VCM and apply in many applications such as surveillance and transportation systems.

In the last part of the talk, we will discuss how the blockchain technology can be applied in video streaming. There is a trend that blockchain technology will change entertainment and streaming industry and will soon completely overthrow the current video streaming. The blockchain technology will allow that the video is decentralized among many nodes, so it can be watched everywhere. We will describe how the decentralized video streaming works and the benefits of the decentralized video streaming.

Part Five   征文

我们邀请大家横跨理论和系统研究，就广泛的研究主题投稿。此会议感兴趣的主题有（包括但不限于）：

信号处理

· 自适应和聚类算法

· 自适应、阵列、多维、光学和非线性信号处理

· 循环平稳分析

· 离散余弦变换

· 离散希尔伯特变换

图像处理

· 3-D和表面重建

· 自动图像和视频注释

· 基于内容的图像检索

· 密码学、隐写术和水印

· 图像编码和压缩

· 图像过滤、平滑和增强

· 图像分割、特征检测与    提取

计算机视觉

· 活动细分

· 仿生视觉

· 手势和活动识别

· 图像和视频采集与形成

· 基于模型的视觉

· 运动分析和对象跟踪

应用

· 增强现实和混合现实

· 自动驾驶汽车

· 生物识别、面部识别

·环境监测

·步态分析、平衡研究、 跌倒检测和预防

·医学图像处理

更多请查看：www.icvisp.org

Part Six 

投稿说明

1. 关于投稿：

网页提交https://cmt3.research.microsoft.com/ICVISP2022

邮箱提交：icvisp@iased.org

2.投稿要求

1) 稿件必须为全英文稿件，图片、表格、公式中均不允许有中文出现。

2) 论文应包含：Abstract（摘要）、Keywords（关键词）、Introduction（引言）、Text（正文）、Conclusion（结论）、References（参考文献）。

3) 所有稿件应为原创，未公开见刊的，论文需要符合主题、论据充分、具备实用价值和创新性。

4) 投稿的文章由评审进行评估，评估内容包括原创性、技术或研究的内容和深度、会议主题相关性、贡献性和可读性