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video cut
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    Stress on the arithmetic of video cut: with keeping the same veracity, reduce resolving power and abstract key color to fall the complexity based on traditional histogram method;
    在传统的基于直方图的视频镜头检测方法基础上,通过降低分辨率和提取主色特征等方法,在保证准确率的前提下降低算法的复杂度;
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  video cut
This paper discusses a video cut detection method.
      
Projection-detecting filter for video cut detection
      
This paper presents a video cut detection algorithm using multi-levelHausdor distance histograms.
      
By combining long-silence detection with video cut detection, only those cuts occurring during silence would have a high confidence score.
      
A video cut can be detected by using color histogram.
      


Various video compressed coding standards are established in the sphere of difference according to people for the requirement of the data of voice and image,and developed continuously along with the demand of people. Now, video compressed coding research divides into two directions mainly:One is that DCT hybrid encoding scheme based on tradition;another is the coding scheme based on object of putting forward based on 2 generation image coding tech- nology. The coding method based on object,can not...

Various video compressed coding standards are established in the sphere of difference according to people for the requirement of the data of voice and image,and developed continuously along with the demand of people. Now, video compressed coding research divides into two directions mainly:One is that DCT hybrid encoding scheme based on tradition;another is the coding scheme based on object of putting forward based on 2 generation image coding tech- nology. The coding method based on object,can not only satisfy the function that gets the requirement of larger image data compression ratio further and can realize man-machine interaction,so we think it will be future video compressed coding develop direction. In this paper,we study selection algorithm of the coding model based on object,and give the method of video cuts apart using the concept of video object in MPEG-4.

各种视频压缩编码标准都是根据人们在不同领域中对声像数据的要求所制定的,并且随着人们的需求不断地发展。目前,视频压缩编码研究主要分为两个方向:一是基于传统的DCT 混合编码方案;另一个是基于第二代图像编码技术而提出的基于对象的编码方案。其中,基于对象的编码方法不仅能满足进一步获得更大的图像数据压缩比的要求,而且能够实现人机对话的功能,所以,我们认为它将是未来视频压缩编码的发展方向。本文对基于对象的编码模式选择算法进行了研究,借用了MPEG-4中视频对象的概念,提出了一种视频分割的方法。

According to the drawbacks of available algorithms, a new hierarchical and multiresolution approach to the detection and classification of scene breaks in video sequences is presented in this paper. This method gives the detection scheme for different shots using different algorithms. This scheme includes four parts: cut detection(video cut), fade detection, dissolve detection and wipe detection. Firstly, the video clips are cut by FCM clustering method, then the fade and dissolve are detected...

According to the drawbacks of available algorithms, a new hierarchical and multiresolution approach to the detection and classification of scene breaks in video sequences is presented in this paper. This method gives the detection scheme for different shots using different algorithms. This scheme includes four parts: cut detection(video cut), fade detection, dissolve detection and wipe detection. Firstly, the video clips are cut by FCM clustering method, then the fade and dissolve are detected using Hausdorff distance and SCD algorithm in the high components and the low components respectively by integer-to-integer wavelet transform. Finally, according to the cut and the former detection of gradual changes, we use a motion vector in high-components of 3D-WT to detect the wipe transition. Experimental results with real video clips demonstrate that our method can detect and classify a variety of scene breaks, including cuts, fades and dissolves, even in sequences involving significant motions and flash.

提出了一种分层的和多分辨的镜头边界检测方法。该方法对各种不同的镜头间过渡类型给出了用不同方法进行联合检测的方案,该方案主要分为突变镜头检测(即视频切分)、淡化过渡检测、溶解过渡检测及划变过渡检测4个部分。检测方案并不是简单地将各种方法拼接在一起,而是通过小波变换的多分辨分析将它们有机地结合起来,相互关联,达到有效检测结果。首先用FCM聚类算法进行视频切分,然后根据聚类结果分别在整数小波分解后的高频部分用Gaussian加权Hausdorff距离结合边界改变率算法检测淡化过渡;对分解后的低频部分用所提出的SCD算法(Similarity of color distribution based method)检测溶解过渡,并通过自适应调节权系数(系数盲调节)使检测相异度函数更能适用于多种视频片段。最后根据切分以及前面两种过渡检测的结果,利用三维小波分解后高频成分中的运动部分所定义的运动矢量来检测划变过渡。用实际视频数据所做的仿真实验结果表明,该方法不但能同时检测突变过渡和渐变过渡,而且能准确地判断渐变过渡的类型及其位置。此外,还能有效地抑制闪光、运动等的影响,从而提高了检测精度。

 
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