会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明授权
    • Distortion/quality measurement
    • 畸变/质量测量
    • US09323997B2
    • 2016-04-26
    • US14358304
    • 2011-11-28
    • Xiaodong GuKai XieZhibo Chen
    • Xiaodong GuKai XieZhibo Chen
    • G06K9/03H04N17/00
    • G06K9/036H04N17/004
    • Various implementations address distortion and quality measurements related to, for example, freeze-with-skip and/or a freeze-without-skip events. In several implementations, information is accessed indicating that a first and second set of one or more consecutive pictures are not to be displayed. A first and second indicator are determined. In one such implementation, the first and second indicators indicate an amount of distortion across one or more types of distortive effects that result from displaying substantially a first, or second, same picture during a display time for the first, or second, set of pictures. The first and second indicators are combined in a non-linear manner. In another such implementation, the distortion is associated with a given type of distortive effect, from among multiple types of distortive effects, and the first and second indicators are combined for the given type of distortive effect.
    • 各种实施方案涉及与例如冻结跳过和/或冻结无跳跃事件相关的失真和质量测量。 在几个实现中,访问指示不显示第一和第二组一个或多个连续图片的信息。 确定第一和第二指示符。 在一个这样的实施方案中,第一和第二指示符指示在一个或多个类型的失真效应的失真量,这是由在第一或第二组图像的显示时间期间显示基本上第一或第二相同图像而导致的 。 第一和第二指标以非线性方式组合。 在另一个这样的实现中,失真与多种类型的失真效应中的给定类型的失真效应相关联,并且对于给定类型的失真效应组合第一和第二指示符。
    • 3. 发明授权
    • Method and apparatus for measuring video quality
    • 用于测量视频质量的方法和装置
    • US08675075B2
    • 2014-03-18
    • US13811657
    • 2010-07-30
    • Xiaodong GuDebing LiuZhibo Chen
    • Xiaodong GuDebing LiuZhibo Chen
    • H04N17/00H04N5/21
    • H04N17/00H04N5/21H04N17/002H04N19/139H04N19/14H04N19/172H04N19/89
    • A method and apparatus for measuring the quality of a video sequence, which includes a plurality of frames, among which one or more consecutive frames are lost, wherein during the displaying of the video sequence, the one or more lost frames are substituted by an immediate preceding frame in the video sequence during a period from the displaying of the immediate preceding frame to that of an immediate subsequent frame of the one or more lost frames, the method includes measuring the quality of the video sequence as a function of a first parameter (DF) relating to the stability of the immediate preceding frame during the period, a second parameter (DD) relating to the continuity between the immediate preceding frame and the immediate subsequent frame, and a third parameter (DP) relating to the coherent 20 motions of the video sequence.
    • 一种用于测量包括多个帧的视频序列的质量的方法和装置,其中一个或多个连续帧丢失,其中在显示视频序列期间,一个或多个丢失帧被立即替换 在从直接前一帧的显示到所述一个或多个丢失帧的即时后续帧的时间段期间,视频序列中的前一帧的视频序列的前一帧,该方法包括测量作为第一参数的函数的视频序列的质量 DF),与第一参数(DP)有关,该第二参数(DD)涉及在紧接着的前一帧与即时后续帧之间的连续性的第二参数(DD)以及与第二参数 视频序列。
    • 4. 发明申请
    • METHOD AND DEVICE FOR DETERMINING A MOTION VECTOR FOR A CURRENT BLOCK OF A CURRENT VIDEO FRAME
    • 用于确定电流视频框架的电流块的运动矢量的方法和装置
    • US20130251045A1
    • 2013-09-26
    • US13991664
    • 2010-12-10
    • Xiaodong GuDebing LiuZhibo Chen
    • Xiaodong GuDebing LiuZhibo Chen
    • H04N7/36
    • H04N19/61H04N19/521H04N19/57
    • A method for determining a motion vector for a current video frame block comprises determining the motion vector using full search. Then, a number of further motion vectors is counted which is the number of motion vectors of neighbouring blocks which are similar to each other and the motion vector. Then it is ascertained that the number meets or exceeds a threshold and that the motion vector is not similar to at least one of the counted further motion vectors. A search region is determined using counted motion vectors and searched for a local best match of the current block. The motion vector is changed towards referencing the local best match. The search region only comprises candidates referenced by motion vector candidates similar to a yet further motion vector pointing to a centre of the further search region. Then, the motion vector resembles the motion presumed by the HVS.
    • 用于确定当前视频帧块的运动矢量的方法包括使用全搜索来确定运动矢量。 然后,计数多个其他运动矢量,它们是彼此相似的相邻块的运动矢量的数量和运动矢量。 然后确定该数量满足或超过阈值,并且运动矢量与所计数的进一步的运动矢量中的至少一个不相似。 使用计数运动矢量确定搜索区域,并搜索当前块的局部最佳匹配。 运动矢量改变为参考局部最佳匹配。 搜索区域仅包括由与指向另外的搜索区域的中心的又一运动矢量类似的运动矢量候选引用的候选者。 然后,运动矢量类似于由HVS假设的运动。
    • 9. 发明授权
    • Method and apparatus for measuring video quality using at least one semi-supervised learning regressor for mean observer score prediction
    • 使用至少一个半监督学习回归器测量视频质量的方法和装置,用于平均观察者评分预测
    • US08824783B2
    • 2014-09-02
    • US13695060
    • 2010-04-30
    • Feng XuZhibo ChenDebing LiuXiaodong Gu
    • Feng XuZhibo ChenDebing LiuXiaodong Gu
    • G06K9/62G06K9/46H04N17/00G06T7/00
    • H04N17/004G06N99/005G06T7/0002G06T2207/10016G06T2207/20081G06T2207/30168
    • The invention is made in the technical field of video quality measurement. More precisely, the invention is related to mean observer score prediction using a trained semi-supervised learning regressor. That is, a method and apparatus for measuring video quality using a semi-supervised learning system for mean observer score prediction is proposed. Said semi-supervised learning system comprises at least one semi-supervised learning regressor and said method comprises training the learning system and retraining the trained learning system using a selection of test data wherein the test data is used for determining at least one mean observer score prediction using the trained learning system and the selection is indicated by a feedback received through a user interface upon presenting, in the user interface, said at least one mean observer score prediction. Doing so, prediction quality can be improved after re-training at least for the selection.
    • 本发明是在视频质量测量技术领域进行的。 更准确地说,本发明涉及使用训练有素的半监督学习回归器的平均观察者评分预测。 也就是说,提出了一种使用半监督学习系统测量视频质量的方法和装置,用于平均观察员评分预测。 所述半监督学习系统包括至少一个半监督学习回归器,并且所述方法包括训练学习系统并且使用测试数据的选择重新训练训练学习系统,其中测试数据用于确定至少一个平均观察者评分预测 使用训练的学习系统和选择由在用户界面中呈现所述至少一个平均观察者分数预测时通过用户界面接收的反馈来指示。 做到这一点,至少在选择后再进行训练后,可以提高预测质量。