In this paper, we present a fast algorithm that automatically detects caption text in MPEG compressed video.
提出了一种在MPEG压缩流上基于模型的快速标题文字探测算法。
The proposed method determines the motion activity and visual content change of the MPEG compressed video by using the luminance DCT DC value, macroblock type and motion vector.
本文算法利用亮度DCTDC值、宏块类型和运动向量来确定MPEG压缩视频中运动活动和视觉内容变化。
In this paper, at first briefly discuss the existing approaches, and then present a motion feature based key frame extracting method using fuzzy reasoning theory for MPEG compressed video.
首先介绍了目前的关键帧提取技术，然后提出了一种基于运动特征利用模糊推理算法从MPEG视频流中提取关键帧的方法。
The simulation results on modeling of MPEG-compressed video traffic demonstrate that TES models are able to characterize the burstiness of network traffic streams.
对MPEG视频业务的建模的仿真结果表明，TES模型能够很好地表征网络业务流的突发性。
The simulation results on modeling of MPEG-compressed video traffic demonstrate that TES models are able to characterize the burstiness of network traffic streams.
对MPEG视频业务的建模的仿真结果表明，TES模型能够很好地表征网络业务流的突发性。
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