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    • 3. 发明授权
    • Albuming method with automatic page layout
    • 具有自动页面布局的相册方法
    • US06636648B2
    • 2003-10-21
    • US09347310
    • 1999-07-02
    • Alexander C. LouiJohn K. McBrideStephen L. ShafferMark D. Wood
    • Alexander C. LouiJohn K. McBrideStephen L. ShafferMark D. Wood
    • G06K936
    • G06T11/60
    • An albuming method includes the automatic adaptation of the page layout of a plurality of images to a boundary condition of an event. The method includes the steps of receiving a plurality of images having event-determining information that relates to one or more events to which the images pertain and the generation of an event boundary based on the on the event-determining information. The images for each event are then laid out into a page format adapted to the event boundary determined for that event. For example, if the page format is determined to have a maximum number of images per page, and if the number of images remaining for the last page are fewer than the maximum number, the page layout of the last or more pages of the event is automatically adapted to the event boundary by, e.g., adjusting the arrangement of the pictures on the last page.
    • 相册方法包括将多个图像的页面布局自动适应于事件的边界条件。 该方法包括以下步骤:基于事件确定信息,接收具有与图像所属的一个或多个事件和事件边界的生成有关的事件确定信息的多个图像。 然后将每个事件的图像布置成适合于为该事件确定的事件边界的页面格式。 例如,如果页面格式被确定为具有每页最大数量的图像,并且如果最后页面剩余的图像数量少于最大数量,则事件的最后或更多页面的页面布局为 通过例如调整最后一页上的图像的布置来自动地适应于事件边界。
    • 7. 发明授权
    • Method for computing scale for tag insertion
    • 计算标签插入尺度的方法
    • US08786889B2
    • 2014-07-22
    • US13598310
    • 2012-08-29
    • Minwoo ParkDhiraj JoshiAlexander C. Loui
    • Minwoo ParkDhiraj JoshiAlexander C. Loui
    • G06K15/00G06F3/12G06K9/20G06K9/34
    • G09G5/006G09G5/26G09G5/40G09G2340/10H04L51/32
    • Computing a scale factor to insert a first set of shapes into a second set of shapes to form a combined image includes receiving the two sets of shapes, using a processor to convert the first set of shapes into a set of rectangles and the second set of shapes into a set of intervals and computing the scale factor for either the set of intervals or the set of rectangles to generate the combined image by iteratively inserting the set of rectangles into the set of intervals and updating the scale factor in response to a residual area or an overflow area until all the rectangles in the set of rectangles have been inserted into the set of intervals and the residual area in the set of intervals is below a threshold, and storing the combined image in memory.
    • 计算比例因子以将第一组形状插入到第二组形状中以形成组合图像包括使用处理器来接收两组形状,以将第一组形状转换为一组矩形,并且第二组 形成一组间隔,并且通过迭代地将该组矩形迭代地插入到该组间隔中并且响应于剩余区域更新比例因子来计算间隔集合或矩形集合的比例因子以生成组合图像 或溢出区域,直到该组矩形中的所有矩形已经被插入到该组间隔中,并且该间隔集合中的剩余区域低于阈值,并将组合的图像存储在存储器中。
    • 9. 发明申请
    • SCENE BOUNDARY DETERMINATION USING SPARSITY-BASED MODEL
    • 使用基于SPARSITY的模型的场景边界确定
    • US20130235275A1
    • 2013-09-12
    • US13413982
    • 2012-03-07
    • Mrityunjay KumarAbdolreza Abdolhosseini MoghadamAlexander C. LouiJiebo Luo
    • Mrityunjay KumarAbdolreza Abdolhosseini MoghadamAlexander C. LouiJiebo Luo
    • H04N5/14
    • H04N5/144G11B27/28H04N21/44008H04N21/8549
    • A method for determining a scene boundary location dividing a first scene and a second scene in an input video sequence. The scene boundary location is determined responsive to a merit function value, which is a function of the candidate scene boundary location. The merit function value for a particular candidate scene boundary location is determined by representing the dynamic scene content for the input video frames before and after candidate scene boundary using sparse combinations of a set of basis functions, wherein the sparse combinations of the basis functions are determined by finding a sparse vector of weighting coefficients for each of the basis functions. The weighting coefficients determined for each of the input video frames are combined to determine the merit function value. The candidate scene boundary providing the smallest merit function value is designated to be the scene boundary location.
    • 一种用于确定在输入视频序列中划分第一场景和第二场景的场景边界位置的方法。 响应于作为候选场景边界位置的函数的优值函数值确定场景边界位置。 通过使用一组基函数的稀疏组合表示候选场景边界之前和之后的输入视频帧的动态场景内容来确定特定候选场景边界位置的优值函数值,其中确定基函数的稀疏组合 通过找出每个基本函数的加权系数的稀疏矢量。 为每个输入视频帧确定的加权系数被组合以确定优值函数值。 提供最小优值函数值的候选场景边界被指定为场景边界位置。
    • 10. 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
    • US20130051670A1
    • 2013-02-28
    • US13221078
    • 2011-08-30
    • Madirakshi DasAlexander C. Loui
    • Madirakshi DasAlexander C. Loui
    • G06K9/46
    • 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; 自动分析所述元数据数据库以识别多个频繁项集,其中所述频繁项集中的每一个是发生在所述数字图像的至少预定义分数中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; 响应于所确定的发生概率,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。