Method and system for comparing video shots

    公开(公告)号:US10354143B2

    公开(公告)日:2019-07-16

    申请号:US15516965

    申请日:2014-10-13

    Abstract: A method (100) for comparing a first video shot (Vs1) comprising a first set of first images (I1(s)) with a second video shot (Vs2) comprising a second set of second images (I2(t)), at least one between the first and the second set comprising at least two images. The method comprises pairing (110) each first image of the first set with each second image of the second set to form a plurality of images pairs (IP(m)), and, for each image pair, carrying out the operations a)-g): a) identifying (120) first interest points in the first image and second interest points in the second image; b) associating (120) first interest points with corresponding second interest points in order to form corresponding interest point matches; c) for each pair of first interest points, calculating (130) the distance therebetween for obtaining a corresponding first length; d) for each pair of second interest points, calculating (130) the distance therebetween for obtaining a corresponding second length; e) calculating a plurality of distance ratios (130), each distance ratio corresponding to a selected pair of interest point matches and being based on a ratio of a first term and a second term or on a ratio of the second term and the first term, said first term corresponding to the distance between the first interest points of said pair of interest point matches and said second term corresponding to the distance between the second interest points of said pair of interest point matches; f) computing (140) a first representation of the statistical distribution of the plurality of calculated distance ratios; g) computing (150) a second representation of the statistical distribution of distance ratios obtained under the hypothesis that all the interest point matches in the image pair are outliers. The method further comprises generating (160) a first global representation of the statistical distribution of the plurality of calculated distance ratios computed for all the image pairs based on the first representations of all the image pairs; generating (170) a second global representation of the statistical distribution of distance ratios obtained under the hypothesis that all the interest point matches in all the image pairs are outliers based on the second representations of all the image pairs; comparing (180) said first global representation with said second global representation, and assessing (190) whether the first video shot contains a view of an object depicted in the second video shot based on said comparison.

    IMAGE ANALYSIS
    12.
    发明申请
    IMAGE ANALYSIS 审中-公开
    图像分析

    公开(公告)号:US20160125261A1

    公开(公告)日:2016-05-05

    申请号:US14991556

    申请日:2016-01-08

    Abstract: A method for processing an image is proposed. The method comprises identifying a first group of keypoints in the image. For each keypoint of the first group, the method provides for identifying at least one corresponding keypoint local feature related to said each keypoint; for said at least one keypoint local feature, calculating a corresponding local feature relevance probability; calculating a keypoint relevance probability based on the local feature relevance probabilities of said at least one local feature. The method further comprises selecting keypoints, among the keypoints of the first group, having the highest keypoint relevance probabilities to form a second group of keypoints, and exploiting the keypoints of the second group for analysing the image. The local feature relevance probability calculated for a local feature of a keypoint is obtained by comparing the value assumed by said local feature with a corresponding reference statistical distribution of values of said local feature.

    Abstract translation: 提出了一种处理图像的方法。 该方法包括识别图像中的第一组关键点。 对于第一组的每个关键点,该方法提供用于识别与所述每个关键点相关的至少一个对应的关键点局部特征; 对于所述至少一个关键点局部特征,计算相应的局部特征相关概率; 基于所述至少一个局部特征的局部特征相关性概率来计算关键点相关概率。 该方法还包括:选择具有最高关键点相关性概率的第一组的关键点中的关键点,以形成第二组关键点,以及利用第二组的关键点来分析图像。 通过将所述局部特征所假设的值与所述局部特征的值的相应参考统计分布进行比较来获得针对关键点的局部特征计算的局部特征相关概率。

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