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    • 7. 发明申请
    • DETECTING SCENE TRANSITIONS IN DIGITAL VIDEO SEQUENCES
    • 检测数字视频序列中的场景转换
    • US20090109341A1
    • 2009-04-30
    • US11927944
    • 2007-10-30
    • Seyfullah Halit OguzAmit RohatgiFang LiuPhanikumar Bhamidipati
    • Seyfullah Halit OguzAmit RohatgiFang LiuPhanikumar Bhamidipati
    • H04N5/21
    • H04N5/147
    • This disclosure describes techniques for detecting scene transitions in a digital video sequence. An encoding device may, for example, analyze a distribution of pixel values over a plurality of frames to detect locations at which the scene transitions occur. In particular, the encoding device analyzes the distribution of pixel locations having values in a mid-range of possible pixel values to identify locations in the plurality of frames that experience a significant short-term increase in the number of pixel locations having mid-range pixel values. A significant short-term increase in the number of pixel locations with pixel values in the mid-range of possible pixel values is indicative of a soft transition. In this manner, occurrences of gradual scene transitions are detected by identifying locations within the plurality of frames that have significant short-term increases in the number of pixel locations having mid-range pixel values.
    • 本公开描述了用于检测数字视频序列中的场景转换的技术。 编码装置可以例如分析多个帧上的像素值的分布,以检测发生场景转换的位置。 特别地,编码装置分析具有在可能像素值的中间范围内的值的像素位置的分布,以识别多个帧中的位置,其经历具有中间像素的像素位置的数量的显着的短期增加 价值观。 在可能的像素值的中间范围内的像素值的像素位置的数量的显着短期增加表示软转换。 以这种方式,通过识别具有中等范围像素值的像素位置的数量的显着短期增加的多个帧内的位置来检测逐渐场景转换的发生。
    • 8. 发明申请
    • ADAPTIVE GROUP OF PICTURES (AGOP) STRUCTURE DETERMINATION
    • 自适应组图(AGOP)结构测定
    • US20090154816A1
    • 2009-06-18
    • US11957582
    • 2007-12-17
    • Scott T. SwazeySeyfullah Halit OguzAmit Rohatgi
    • Scott T. SwazeySeyfullah Halit OguzAmit Rohatgi
    • G06K9/36
    • H04N19/40H04N19/114H04N19/142H04N19/177H04N19/61H04N19/87
    • This disclosure is directed to techniques for determining a picture type for each of a plurality of frames included in a video sequence based on cross-correlations between the frames. The cross-correlations include first order cross-correlations between image information within pairs of frames included in the video sequence and second order cross-correlations between pairs of the first order cross-correlations. The first order cross-correlations may be analyzed to detect video transitional effects between the frames. The first and second order cross-correlations may be comparatively analyzed to determine temporal similarities between the frames. Therefore, the correlation-based determination techniques determine picture types for the frames based on the video transitional effects and the temporal similarities. The correlation-based determination techniques may calculate the first order cross-correlations between images within pairs of frames, or between sets of subimages within pairs of frames that are then averaged over the subimages for each of the pairs of frames.
    • 本公开涉及用于基于帧之间的互相关来确定包括在视频序列中的多个帧中的每一个的图像类型的技术。 互相关包括在视频序列中包括的帧内的图像信息之间的第一级互相关和第一级互相关对之间的二阶交叉相关。 可以分析第一级互相关以检测帧之间的视频过渡效应。 可以相对分析第一和第二阶互相关以确定帧之间的时间相似性。 因此,基于相关的确定技术基于视频过渡效应和时间相似性确定帧的图像类型。 基于相关的确定技术可以计算帧对之间的图像之间的第一阶交叉相关性,或者在帧对之间的子图像集合之间的第一阶交叉相关性,然后对于每对帧对于子图像进行平均。