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.
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.
百度学术
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