Method for automatically classifying images into events in a multimedia authoring application
    94.
    发明授权
    Method for automatically classifying images into events in a multimedia authoring application 有权
    用于在多媒体创作应用程序中自动将图像分类为事件的方法

    公开(公告)号:US06865297B2

    公开(公告)日:2005-03-08

    申请号:US10706145

    申请日:2003-11-12

    IPC分类号: G06K9/00 G06K9/62

    CPC分类号: G06K9/0063

    摘要: A method for automatically classifying images into events for composing and authoring of a multimedia image program on a recordable optical disc comprises the steps of: (a) receiving a plurality of images having either or both date and/or time of image capture; (b) determining one or more largest time differences of the plurality of images based on clustering of the images; (c) separating the plurality of images into events based on having one or more boundaries between events which one or more boundaries correspond to the one or more largest time differences; (d) specifying at least one multimedia feature that is related to each event; (e) encoding the images between event boundaries and the at least one multimedia feature associated therewith into an event bitstream; and (f) writing each event bitstream to the recordable optical disc, whereby each event is authored into a separate section of the recordable optical disc.

    摘要翻译: 一种用于将图像自动分类为用于在可记录光盘上构建和创作多媒体图像程序的事件的方法包括以下步骤:(a)接收具有图像捕获的日期和/或时间中的任一个或两个的多个图像; (b)基于所述图像的聚类来确定所述多个图像中的一个或多个最大时间差; (c)基于在所述一个或多个边界对应于所述一个或多个最大时间差的事件之间具有一个或多个边界,将所述多个图像分离成事件; (d)指定与每个事件相关的至少一个多媒体特征; (e)将事件边界和与其相关联的至少一个多媒体特征之间的图像编码为事件比特流; 和(f)将每个事件比特流写入可记录光盘,由此每个事件被写入可记录光盘的单独部分。

    Method and system for segmenting and identifying events in images using spoken annotations
    95.
    发明授权
    Method and system for segmenting and identifying events in images using spoken annotations 有权
    使用语音注释分割和识别图像中的事件的方法和系统

    公开(公告)号:US06810146B2

    公开(公告)日:2004-10-26

    申请号:US09872593

    申请日:2001-06-01

    IPC分类号: G06K934

    CPC分类号: G06F17/30265

    摘要: A method for automatically organizing digitized photographic images into events based on spoken annotations comprises the steps of: providing natural-language text based on spoken annotations corresponding to at least some of the photographic images; extracting predetermined information from the natural-language text that characterizes the annotations of the images; segmenting the images into events by examining each annotation for the presence of certain categories of information which are indicative of a boundary between events; and identifying each event by assembling the categories of information into event descriptions. The invention further comprises the step of summarizing each event by selecting and arranging the event descriptions in a suitable manner, such as in a photographic album.

    摘要翻译: 一种基于语音注释自动将数字化摄影图像组织成事件的方法包括以下步骤:基于与至少一些摄影图像对应的语音注释提供自然语言文本; 从表示图像的注释的自然语言文本中提取预定信息; 通过检查每个注释来存在指示事件之间的边界的某些类别的信息来将图像分割成事件; 以及通过将信息的类别组合成事件描述来识别每个事件。 本发明还包括通过以合适的方式(例如在照相册)中选择和布置事件描述来概括每个事件的步骤。

    Video representation using a sparsity-based model
    96.
    发明授权
    Video representation using a sparsity-based model 有权
    使用基于稀疏模型的视频表示

    公开(公告)号:US08982958B2

    公开(公告)日:2015-03-17

    申请号:US13413962

    申请日:2012-03-07

    摘要: A method for representing a video sequence including a time sequence of input video frames, the input video frames including some common scene content that is common to all of the input video frames and some dynamic scene content that changes between at least some of the input video frames. Affine transform are determined to align the common scene content in the input video frames. A common video frame including the common scene content is determined by forming a sparse combination of a first basis functions. A dynamic video frame is determined for each input video frame by forming a sparse combination of a second basis functions, wherein the dynamic video frames can be combined with the respective affine transforms and the common video frame to provide reconstructed video frames.

    摘要翻译: 一种用于表示包括输入视频帧的时间序列的视频序列的方法,所述输入视频帧包括所有输入视频帧共同的一些常见场景内容和在至少一些输入视频之间改变的一些动态场景内容 框架。 确定仿射变换以使输入视频帧中的公共场景内容对齐。 通过形成第一基本函数的稀疏组合来确定包括公共场景内容的公共视频帧。 通过形成第二基本函数的稀疏组合,为每个输入视频帧确定动态视频帧,其中动态视频帧可以与各自的仿射变换和公共视频帧组合以提供重构的视频帧。

    Estimating the clutter of digital images
    97.
    发明授权
    Estimating the clutter of digital images 有权
    估计数字图像的杂乱

    公开(公告)号:US08731291B2

    公开(公告)日:2014-05-20

    申请号:US13624985

    申请日:2012-09-24

    IPC分类号: G06K9/00

    CPC分类号: G06K9/00664

    摘要: A method for determining an estimated clutter level of an input digital image based on an inequality index. The inequality index is determined by partitioning the input digital image into small sub-images and analyzing the sub-images to determine a set of image features. The image features are associated with a set of designated reference features, and the inequality index is determined based on the statistical variation of the reference features. The inequality index is compared to a predefined threshold to classify the input digital image as a rich-content image or a low-content image. For rich-content images, the estimated clutter level is determined responsive to a set of scene content features relating to spatial structures or semantic content of the input digital image is determined by analyzing the input digital image. For low-content images, the estimated clutter level is determined responsive to an overall luminance level.

    摘要翻译: 一种用于基于不等式指数来确定输入数字图像的估计杂波电平的方法。 通过将输入的数字图像分割成小的子图像并分析子图像来确定一组图像特征来确定不等式索引。 图像特征与一组指定的参考特征相关联,并且基于参考特征的统计变化来确定不等式指数。 将不等式指数与预定阈值进行比较,以将输入数字图像分类为富内容图像或低内容图像。 对于富含内容的图像,响应于与输入数字图像的空间结构或语义内容相关的一组场景内容特征来确定估计的杂波水平,通过分析输入的数字图像来确定。 对于低内容图像,估计的杂波电平是根据整体亮度水平确定的。

    DETERMINING THE ESTIMATED CLUTTER OF DIGITAL IMAGES
    98.
    发明申请
    DETERMINING THE ESTIMATED CLUTTER OF DIGITAL IMAGES 有权
    确定数字图像的估计转折

    公开(公告)号:US20140086495A1

    公开(公告)日:2014-03-27

    申请号:US13624986

    申请日:2012-09-24

    IPC分类号: G06K9/68

    CPC分类号: G06K9/00664

    摘要: A method for determining an estimated clutter level of an input digital image based on an inequality index. The inequality index is determined by analyzing the input digital image to determine a set of image features. The image features are associated with a set of designated reference features, and the inequality index is determined based on the statistical variation of the reference features. A set of scene content features relating to spatial structures or semantic content of the input digital image is determined by analyzing the input digital image. The estimated clutter is determined responsive to the inequality index and the scene content features.

    摘要翻译: 一种用于基于不等式指数来确定输入数字图像的估计杂波电平的方法。 通过分析输入数字图像来确定一组图像特征来确定不等式指数。 图像特征与一组指定的参考特征相关联,并且基于参考特征的统计变化来确定不等式指数。 通过分析输入数字图像来确定与输入数字图像的空间结构或语义内容相关的一组场景内容特征。 响应于不等式指数和场景内容特征确定估计的杂波。

    ESTIMATING THE CLUTTER OF DIGITAL IMAGES
    99.
    发明申请
    ESTIMATING THE CLUTTER OF DIGITAL IMAGES 有权
    估计数字图像的转换

    公开(公告)号:US20140086487A1

    公开(公告)日:2014-03-27

    申请号:US13624985

    申请日:2012-09-24

    IPC分类号: G06K9/62

    CPC分类号: G06K9/00664

    摘要: A method for determining an estimated clutter level of an input digital image based on an inequality index. The inequality index is determined by partitioning the input digital image into small sub-images and analyzing the sub-images to determine a set of image features. The image features are associated with a set of designated reference features, and the inequality index is determined based on the statistical variation of the reference features. The inequality index is compared to a predefined threshold to classify the input digital image as a rich-content image or a low-content image. For rich-content images, the estimated clutter level is determined responsive to a set of scene content features relating to spatial structures or semantic content of the input digital image is determined by analyzing the input digital image. For low-content images, the estimated clutter level is determined responsive to an overall luminance level.

    摘要翻译: 一种用于基于不等式指数来确定输入数字图像的估计杂波电平的方法。 通过将输入的数字图像分割成小的子图像并分析子图像来确定一组图像特征来确定不等式索引。 图像特征与一组指定的参考特征相关联,并且基于参考特征的统计变化来确定不等式指数。 将不等式指数与预定阈值进行比较,以将输入数字图像分类为富内容图像或低内容图像。 对于富含内容的图像,响应于与输入数字图像的空间结构或语义内容相关的一组场景内容特征来确定估计的杂波水平,通过分析输入的数字图像来确定。 对于低内容图像,估计的杂波电平是根据整体亮度水平确定的。

    System For Generating Tag Layouts
    100.
    发明申请
    System For Generating Tag Layouts 有权
    用于生成标签布局的系统

    公开(公告)号:US20140063556A1

    公开(公告)日:2014-03-06

    申请号:US13598260

    申请日:2012-08-29

    IPC分类号: G06K9/36 G06K15/02

    摘要: Generating a tag layout from a set of tags and an ordering of the set of tags, wherein each tag includes a text label and a size for the text label, is disclosed. The system includes a processor accessible memory for receiving an ordered set of tags, each tag including a text label and a size for the text label, and at least one closed shape corresponding to a space for the tag layout. The system further includes a processor for generating the tag layout by computing a scale factor for either the closed shape or the size of the text labels in the set of tags such that all the tags in the set of tags fit within the closed shape, and the processor stores the generated tag layout in the memory.

    摘要翻译: 公开了一组标签生成标签布局以及该标签集的顺序,其中每个标签包括文本标签和文本标签的尺寸。 该系统包括用于接收有序集合标签的处理器可访问存储器,每个标签包括文本标签和文本标签的尺寸,以及至少一个对应于标签布局的空间的封闭形状。 该系统还包括一个处理器,用于通过计算一组标签中的封闭形状或文本标签的尺寸的比例因子来生成标签布局,使得该组标签中的所有标签都适合于闭合形状,以及 处理器将生成的标签布局存储在存储器中。