ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2017, Vol. 54 ›› Issue (6): 1225-1237.doi: 10.7544/issn1000-1239.2017.20170001

所属专题: 2017优青专题

• 综述 • 上一篇    下一篇

高通量图像视频计算

唐金辉1,李泽超1,刘少礼2,秦磊2   

  1. 1(南京理工大学计算机科学与工程学院 南京 210094); 2(中国科学院计算技术研究所 北京 100190) (jinhuitang@njust.edu.cn)
  • 出版日期: 2017-06-01
  • 基金资助: 
    国家“九七三”重点基础研究发展计划基金项目(2014CB347600);国家自然科学基金项目(61402228);国家自然科学基金优秀青年科学基金项目(61522203)

High-Throughput Image and Video Computing

Tang Jinhui1, Li Zechao1, Liu Shaoli2, Qin Lei2   

  1. 1(School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094); 2(Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190)
  • Online: 2017-06-01

摘要: 互联网上的图像和视频数据正在飞速地产生和传播.这些数据不仅规模庞大,还具有高并发、高维度、大流量的显著特性,导致了目前对它们的实时分析和处理面临着巨大的挑战.这就需要开展高通量图像视频计算方面的研究,需要结合新型硬件结构,利用其体系结构优势,提出一系列实用的高通量图像视频计算理论与方法,提升数据中心的图像视频数据处理效率.为此,在详细地分析了现有的高通量图像视频计算相关方法与技术的基础上,探讨了现有高通量图像视频计算方法研究的不足;进一步地,分析了高通量图像视频计算的3个未来研究方向:高通量图像视频计算理论、高通量图像视频分析方法及高通量视频编码方法.最后,总结了高通量图像视频计算需要解决的3个关键科学问题.这些问题的解决将为互联网图像视频内容监管、大规模视频监控、图像视频搜索等重要应用提供关键技术支持.

关键词: 图像分析, 视频分析, 高通量, 视频编码, 视频计算

Abstract: In recent years, image and video data grows and spreads rapidly in the Internet. The data not only has huge amount, but also has the characteristics of high concurrency, high dimension and high throughput, which brings huge challenges into the real-time analysis and processing of them. To promote the image and video data processing efficiency of big data platforms, it is necessary and important to study the task of high-throughput image and video computing, and propose a series of high-throughput image and video computing theories and methods by considering the new hardware structures. Towards this end, this work first overviews previous high-throughput image and video computing theories and methods in details, and then discusses the disadvantages of the existing high-throughput image and video computing methods. Furthermore, this work analyzes three research directions of the high-throughput image and video computing task in future: the high-throughput image and video computing theories, the high-throughput image and video analysis methods, and the high-throughput video coding methods. Finally, this work introduces three key scientific problems of high-throughput image and video computing. The solutions of these problems will provide key technical support for the applications of content monitoring of Internet images and videos, the large-scale video surveillance, and the image and video search.

Key words: image analysis, video analysis, high throughput, video coding, visual computing

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