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    • 4. 发明申请
    • DETECTING RECURRING THEMES IN CONSUMER IMAGE COLLECTIONS
    • 检测消费者图像收集中的重要问题
    • WO2013032755A1
    • 2013-03-07
    • PCT/US2012/051541
    • 2012-08-20
    • EASTMAN KODAK COMPANYDAS, MadirakshiLOUI, Alexander C.
    • DAS, MadirakshiLOUI, Alexander C.
    • G06F17/30
    • G06K9/6212G06F17/30056G06F17/30265
    • A method of identifying groups of related digital images in a digital image collection, comprising: analyzing each of the digital images to generate associated feature descriptors related to image content or image capture conditions; storing the feature descriptors associated with the digital images in a metadata database; automatically analyzing the metadata database to identify a plurality of frequent itemsets, wherein each of the frequent itemsets is a co- occurring feature descriptor group that occurs in at least a predefined fraction of the digital images; determining a probability of occurrence for each the identified frequent itemsets; determining a quality score for each of the identified frequent itemsets responsive to the determined probability of occurrence; ranking the frequent itemsets based at least on the determined quality scores; and identifying one or more groups of related digital images corresponding to one or more of the top ranked frequent itemsets.
    • 一种在数字图像集合中识别相关数字图像组的方法,包括:分析每个数字图像以生成与图像内容或图像捕获条件相关的相关联的特征描述符; 将与数字图像相关联的特征描述符存储在元数据数据库中; 自动分析元数据数据库以识别多个频繁项集,其中每个频繁项集是在数字图像的至少预定义分数中发生的共同出现的特征描述符组; 确定每个所识别的频繁项集的出现概率; 响应于确定的发生概率确定每个所识别的频繁项集的质量得分; 至少基于确定的质量得分对频繁项集进行排序; 以及识别与一个或多个最高排名的频繁项集相对应的一组或多组相关数字图像。
    • 7. 发明申请
    • ADDITIVE CLUSTERING OF IMAGES LACKING TEMPORAL INFORMATION
    • 图像的附加聚类缺少时间信息
    • WO2006096384A1
    • 2006-09-14
    • PCT/US2006/006990
    • 2006-02-24
    • EASTMAN KODAK COMPANYDAS, MadirakshiLOUI, Alexander C.
    • DAS, MadirakshiLOUI, Alexander C.
    • G06F17/30
    • G06F17/30256G06F17/30265
    • A database has chronologically ordered images classified into event groups based upon a time difference threshold, and into subgroups based upon a similarity measure. In a method and system for combining new images into such a database, new image are ordered into clusters based upon assessed image features. A representative image is selected in each cluster. A database segment chronologically overlapping the new images is designated and a set of database images similar to each representative image are identified in the segment. Different subgroups including one or more retrieved images are associated with each of cluster to provide matched subgroups. The new images are assigned to matched subgroups associated with respective clusters.
    • 数据库根据时差阈值按时间顺序排列成事件组的图像,并且基于相似性度量进入子组。 在将新图像组合到这样的数据库中的方法和系统中,基于评估的图像特征将新图像排序成簇。 在每个集群中选择一个代表性的图像。 指定与时间顺序重叠新图像的数据库段,并且在段中识别与每个代表图像相似的一组数据库图像。 包括一个或多个检索到的图像的不同子组与每个簇相关联以提供匹配的子组。 将新图像分配给与相应簇相关联的匹配子组。