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综合利用了MPEG视频流P帧的运动特征、像素差和直方图差特征,提出了一种基于Rough Set的镜头分割方法。该方法首先提取视频流中P帧的宏块信息,然后分析得到其运动活力性、宏块类型和运动空间分布,再结合这些帧的像素差特征和直方图差特征,利用Rough Set对这些特征进行约减后,对镜头切换处进行识别。实验表明,该方法能有效地区分镜头的突变,对渐变也能很好地检测。 相似文献
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提出了一种新的MPEG压缩视频镜头切换检测算法。该方法通过分析切换点附近各帧的宏块类型特征,引入了一种新的“宏块类型匹配符”(MTMO),使用其在宏块级别上度量子图片组(SGOP)内部各帧之间的差异性,并结合一种自适应阈值选取技术,完成镜头切换检测。实验结果表明,所提算法适用于不同SGOP结构的MPEG视频序列,查全率达99%,准确率达95%。 相似文献
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在视频编码新标准H.264中,一个16×16的帧间编码宏块可采用多种宏块分割模式来进行运动估计,其运动矢量场也更为精细。根据其运动矢量的邻域相关性提出了一种有效的运动矢量修复算法,可在压缩视频流在Internet上进行传输时发生丢包后,通过受损宏块时空域相邻宏块相关信息对丢失的运动矢量进行修复,并针对连续图像片丢失或整帧丢失情况进行处理。仿真实验表明,该方法可有效地抑制视频差错扩散,改善视频质量。 相似文献
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基于统计特征的镜头边缘侦测 总被引:1,自引:0,他引:1
通过分析MPEG视频流中I帧的8×8DCT编码块的DC系数的统计特征,用每个88 DCT编码块的DC系数计算I帧图象的亮度、行列直方图,比较I帧之间直方图的差异,直接从原始的MPEG视频流中侦测镜头切换点. 相似文献
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帧间块模式选择是H.264视频编码器巾比较耗时的模块之一,为降低H.264视频编码器帧间模式选择的复杂度,提出了一种利用宏块的时空相关性实现帧间模式快速选择的方法.该算法通过对视频序列连续帧的时间相关性和相邻宏块的空间相关性进行统计、分析,首先得到宏块模式转换的统计分布规律,并根据此规律得到宏块的初始候选模式;然后利用基于主宏块的宏块跟踪,找到最相关宏块,再由率失真门限筛选出最佳编码模式.仿真实验结果表明,该快速模式选择算法可以在保证视频编码质量的同时,很大程度上降低了编码器的计算复杂度,平均节省编码时间约64%,平均信噪比下降约0.31 dB. 相似文献
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基于DC系数和运动矢量的快速场景分割算法 总被引:1,自引:0,他引:1
场景分割技术是动态视频分析和基于内容的视频检索的基础,以检测出来的场景作为基本单元,可以进一步对视频内容进行分析和建立索引.本文旨在提出一种基于MPEG压缩视频流的场景分割算法,利用MPEG数据流中已有的DCT DC系数和运动矢量,来检测场景的变换,从而实现场景分割,针对实际视频流中场景突变和渐变两类变换.本文提出两种方法分别处理不同情况,对于突变检测,该算法可以定位到帧,由于该算法进行最小程度的解码,降低了计算复杂度,因而大大提高了检测速度. 相似文献
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跳帧转码的运动矢量合成研究 总被引:2,自引:0,他引:2
由于终端设备、通信网络的异构性,视频服务需要提供跳帧转码功能,而直接使用输入码流运动矢量的视频跳帧算法导致视频质量下降严重.在前向主导运动矢量选择算法的基础上,讨论了运动矢量合成时运动矢量越界和主导帧内块不同处理方法对视频质量的影响,提出基于帧内刷新结构的前向主导运动矢量选择算法.实验结果表明,该算法可以有效阻断错误漂移,降低码率,提高视频质量. 相似文献
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多视点彩色视频与深度视频作为多媒体系统中主流3D场景表示方式,吸引了越来越多人的关注。深度视频反映场景的几何信息,如何对其进行快速编码尤为重要。提出了一种基于区域划分的深度视频快速编码算法。首先,根据深度视频的边缘和运动属性把深度视频分为四个区域;然后,深入分析不同区域内宏块模式分布比例以及参考帧选择特性,设计了不同的宏块模式选择和参考帧搜索策略来提高编码速度;最后,测试提出算法的编码时间、码率以及合成虚拟视点的质量。实验结果表明,提出算法在保证虚拟视点图像质量和编码码率基本不变的情况下,节约了85.73%~91.06%的编码时间。 相似文献
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Distributed video coding (DVC) is an emerging video coding technology that utilises the distributed source coding principles to build very low cost video encoders, yet with remarkable error resilience. In the most common DVC framework, the reconstruction function plays a vital role that has a direct impact on the output video quality. In this study, a novel algorithm is proposed for the reconstruction function, particularly focusing on a unidirectional DVC architecture. The proposed technique exploits the variations of the bit error rate of the Wyner-Ziv decoded bit stream and the assumed noise model in the side information stream. The simulation results show that the proposed algorithm yields a significant improvement of the objective and subjective video quality at no additional bit rate cost. 相似文献
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Hongliang Li Guizhong Liu Zhongwei Zhang Yongli Li 《Multimedia, IEEE Transactions on》2004,6(4):624-633
Several scene-detection algorithms, which are only based on bit rate fluctuations, have been proposed. All of them are presented on the fixed thresholds, which are obtained by the empirical records of the video characteristics. Due to the sensitivity of these methods to the accuracy of the records, which are generally obtained by testing several values repeatedly, bad performance evaluation might be observed for the actual scene detection, especially for real-time video traffic. In this paper, we review the previous works in this area, and study the correlation between the scene duration and the scene change at the frame level, and simultaneously investigate the local statistical characteristics of scenes such as variance and peak bit rate etc. Based on this analysis, an effective decision function is first constructed for the scene segmentation. Then, we propose a scene-detection algorithm using the defined dynamic threshold model, which can capture the statistical properties of the scene changes. Experimental results using 15 variable bit rate MPEG video traces indicate good performances of the proposed algorithm with significantly improved scene-detection accuracy. 相似文献
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Huey-Min Sun 《Multimedia Tools and Applications》2014,69(3):1021-1040
Most studies of smoothing video stream compute the required bit rate of video transmission to satisfy all the transmitted data. In this paper, our proposed online smoothing with tolerable data dropping algorithm can adjust the bit rate as smooth as possible. Several multimedia encoding schemes, such as advanced video coding (AVC), can support partial data dropping to adapt to available bandwidth network. The AVC stream can be adapted by smoothing algorithm to ensure video quality for a given set of constraints where these constraints may be either static after the session set up or may dynamically change over the session duration. Our algorithm is based on the online minimum variance bandwidth allocation algorithm to look ahead a window of frames, dynamically adjusting the required bit rate such that ensuring smoothness when the buffer encounters underflow or overflow for video stream. Furthermore, we add the scheme of data dropping into this algorithm to increase the possibility of smoothing bit rates. The experimental results show the peak rate, the average ratio of dropped data, and the coefficient of variation for five test sequences with different content characteristics such as the average frame size, the peak/mean ratio of frame size, and the average frame bit rate. Experimental parameters are varied by window sizes and tolerable dropping ratios. The algorithm can significantly reduce the peak rate and the coefficient of variation when the transmitted packets are allowed dropping by a user-defined dropping ratio. 相似文献
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介绍了一种对MPEG VIDEO码流中场景切换点进行高速检出的新方法,在计算各帧相对于预测帧的类似度之后进行了类似度的归一化,降低了cut检出算法的复杂度,提高了检出的速度。 相似文献
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H.264/AVC QCIF视频场景切换检测是视频应用中一个极具挑战性的研究课题,只利用宏块信息很难得到满意的检测效果,为此提出了一种采用动态阈值和AC相似度的H.264/AVC视频场景切换检测算法,考虑编码预测模式和DCT系数等信息,提出基于编码比特数的动态阈值和基于AC能量的AC图像相似性两个判决准则,据此进行视频场景切换检测。实验结果表明,在高速运动及场景切换频繁的视频上场景切换检测率得到提高,性能也优于现有的算法。 相似文献
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将帧率变换技术与新型视频压缩编码标准HEVC相结合有利于提升视频的压缩效率。针对直接利用HEVC码流信息中的低帧率视频的运动矢量进行帧率上变换时效果不理想的问题,文中提出了一种基于运动矢量细化的帧率上变换与HEVC结合的视频压缩算法。首先,在编码端对原始视频进行抽帧,降低视频帧率;其次,对低帧率视频进行HEVC编解码;然后,在解码端与从HEVC码流中提取出的运动矢量相结合,利用前向-后向联合运动估计对其进行进一步的细化,使细化后的运动矢量更加接近于对象的真实运动;最后,利用基于运动补偿的帧率上变换技术将视频序列恢复至原始帧率。实验结果表明,与HEVC标准相比,所提算法在同等视频质量下可节省一定的码率。同时,与其他算法相比,在节省码率相同的情况下,所提算法重建视频的PSNR值平均可提升0.5 dB。 相似文献
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Browsing video scenes is just the process to unfold the story scenarios of a long video archive, which can help users to locate their desired video segments quickly and efficiently. Automatic scene detection of a long video stream file is hence the first and crucial step toward a concise and comprehensive content-based representation for indexing, browsing and retrieval purposes. In this paper, we present a novel scene detection scheme for various video types. We first detect video shot using a coarse-to-fine algorithm. The key frames without useful information are detected and removed using template matching. Spatio-temporal coherent shots are then grouped into the same scene based on the temporal constraint of video content and visual similarity of shot activity. The proposed algorithm has been performed on various types of videos containing movie and TV program. Promising experimental results shows that the proposed method makes sense to efficient retrieval of video contents of interest. 相似文献