Fast and robust object-extraction framework for object-based streaming system

Ashraf M. A. Ahmad, Suh-Yin Lee
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引用次数: 3

Abstract

Video streaming poses significant technical challenges in the quality of service guarantee and efficient resource management. In this paper, we propose an efficient moving object-extraction algorithm suitable for real-time content-based multimedia streaming systems. A motion vector based object extraction is used to dynamically detect the objects. To utilise the bandwidth efficiently, the video objects can be detected in real time, encoded, and transmitted with higher quality and a higher frame rate than those in the background. To meet the real-time requirement, no computationally intensive operation is included in this framework. Moreover, to guarantee the highest speed, the entire implementation is operating in the compressed domain without any need for decompression.
基于对象流系统的快速鲁棒对象提取框架
视频流在服务质量保证和资源高效管理方面提出了重大的技术挑战。本文提出了一种适用于基于实时内容的多媒体流系统的高效运动对象提取算法。采用基于运动矢量的目标提取方法对目标进行动态检测。为了有效地利用带宽,可以对视频对象进行实时检测、编码,并以比后台更高的质量和帧率进行传输。为了满足实时性要求,该框架中不包含计算密集型操作。此外,为了保证最高的速度,整个实现在压缩域中运行,不需要任何解压缩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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