Computing visual and textual summaries for tagged image collections
    1.
    发明授权
    Computing visual and textual summaries for tagged image collections 有权
    为标记的图像集合计算视觉和文本摘要

    公开(公告)号:US09092673B2

    公开(公告)日:2015-07-28

    申请号:US12436783

    申请日:2009-05-07

    IPC分类号: G06K9/62 G06K9/00 G06F17/30

    摘要: Described is a technology for computing visual and textual summaries for tagged image collections. Heterogeneous affinity propagation is used to together identify both visual and textual exemplars. The heterogeneous affinity propagation finds the exemplars for relational heterogeneous data (e.g., images and words) by considering the relationships (e.g., similarities) within pairs of images, pairs of words, and relationships of words to images (affinity) in an integrated manner.

    摘要翻译: 描述了一种用于计算标记图像集合的视觉和文本摘要的技术。 非均匀亲和度传播用于一起识别视觉和文本样本。 通过考虑图像成对,单词之间的关系(例如,相似度)和单词与图像的关系(亲和性)以集成的方式,异构亲和度传播找到关系异构数据(例如,图像和单词)的示例。

    Optimized KD-tree for scalable search
    2.
    发明授权
    Optimized KD-tree for scalable search 有权
    用于可扩展搜索的优化KD树

    公开(公告)号:US08645380B2

    公开(公告)日:2014-02-04

    申请号:US12940880

    申请日:2010-11-05

    IPC分类号: G06F17/30

    CPC分类号: G06F17/3028 G06F17/30333

    摘要: Techniques for constructing an optimized kd-tree are described. In an implementation, an optimized kd-tree process receives input of a set of data points applicable for large-scale computer vision applications. The process divides the set of the data points into subsets of data points with nodes while generating hyperplanes (e.g., coordinate axes). The process identifies a partition axis for each node based on the coordinate axes combined in a binary way. The optimized kd-tree process creates an optimized kd-tree that organizes the data points based on the identified partition axis. The organization of the data points in the optimized kd-tree provides efficient indexing and searching for a nearest neighbor.

    摘要翻译: 描述了构建优化的kd-tree的技术。 在一个实现中,优化的kd-tree过程接收适用于大规模计算机视觉应用的一组数据点的输入。 该过程在产生超平面(例如,坐标轴)的同时将数据点的集合划分成具有节点的数据点的子集。 该过程基于以二进制方式组合的坐标轴来识别每个节点的分区轴。 优化的kd-tree过程创建一个优化的kd-tree,它根据识别的分区轴组织数据点。 优化的kd-tree中数据点的组织为最近邻居提供了有效的索引和搜索。

    Interactively ranking image search results using color layout relevance
    3.
    发明授权
    Interactively ranking image search results using color layout relevance 有权
    使用颜色布局相关性对图像搜索结果进行交互排序

    公开(公告)号:US08406573B2

    公开(公告)日:2013-03-26

    申请号:US12341953

    申请日:2008-12-22

    IPC分类号: G06K9/60

    CPC分类号: G06K9/00624 G06F17/3025

    摘要: This disclosure describes various exemplary user interfaces, methods, and computer program products for the interactively ranking image search results refinement method using a color layout. The method includes receiving a text query for an image search, presenting image search results in a structured presentation based on the text query and information from an interest color layout. The process creates image search results that may be selected by the user based on color selection palettes or color layout specification schemes. Then the process ranks the image search results by sorting the results according to similarity scores between color layouts from the image search results and the interest color layout from a user based on the color selection palettes and the color layout specification schemes.

    摘要翻译: 本公开描述了使用颜色布局的用于交互式排序的图像搜索结果细化方法的各种示例性用户界面,方法和计算机程序产品。 该方法包括接收用于图像搜索的文本查询,基于文本查询和来自兴趣颜色布局的信息在结构化表示中呈现图像搜索结果。 该过程创建可以由用户基于颜色选择调色板或颜色布局规范方案来选择的图像搜索结果。 然后,该过程通过根据来自图像搜索结果的颜色布局与基于颜色选择调色板和颜色布局规范方案的用户的兴趣颜色布局之间的相似性分数来排序结果来排序图像搜索结果。

    Intelligent image search results summarization and browsing
    4.
    发明授权
    Intelligent image search results summarization and browsing 有权
    智能图像搜索结果汇总和浏览

    公开(公告)号:US08774526B2

    公开(公告)日:2014-07-08

    申请号:US12701969

    申请日:2010-02-08

    摘要: Techniques for intelligent image search results summarization and browsing scheme are described. Images having visual attributes are evaluated for similarities based in part on their visual attributes. At least one preference score indicating a probability of an image to be selected into a summary is calculated for each image. Images are selected based on the similarity of the selected images to the other images and the preference scores of the selected images. A summary of the plurality of images is generated including the selected one individual image.

    摘要翻译: 描述了智能图像搜索结果汇总和浏览方案的技术。 根据其视觉属性,对具有视觉属性的图像进行相似度的评估。 针对每个图像计算指示将图像选择为概要的概率的至少一个偏好分数。 基于所选择的图像与其他图像的相似度以及所选图像的偏好分数来选择图像。 生成包括所选择的一个单独图像的多个图像的概要。

    Optimized KD-Tree for Scalable Search
    5.
    发明申请
    Optimized KD-Tree for Scalable Search 有权
    用于可扩展搜索的优化KD树

    公开(公告)号:US20120117122A1

    公开(公告)日:2012-05-10

    申请号:US12940880

    申请日:2010-11-05

    IPC分类号: G06F17/30

    CPC分类号: G06F17/3028 G06F17/30333

    摘要: Techniques for constructing an optimized kd-tree are described. In an implementation, an optimized kd-tree process receives input of a set of data points applicable for large-scale computer vision applications. The process divides the set of the data points into subsets of data points with nodes while generating hyperplanes (e.g., coordinate axes). The process identifies a partition axis for each node based on the coordinate axes combined in a binary way. The optimized kd-tree process creates an optimized kd-tree that organizes the data points based on the identified partition axis. The organization of the data points in the optimized kd-tree provides efficient indexing and searching for a nearest neighbor.

    摘要翻译: 描述了构建优化的kd-tree的技术。 在一个实现中,优化的kd-tree过程接收适用于大规模计算机视觉应用的一组数据点的输入。 该过程在产生超平面(例如,坐标轴)的同时将数据点的集合划分成具有节点的数据点的子集。 该过程基于以二进制方式组合的坐标轴来识别每个节点的分区轴。 优化的kd-tree过程创建一个优化的kd-tree,它根据识别的分区轴组织数据点。 优化的kd-tree中数据点的组织为最近邻居提供了有效的索引和搜索。

    Intelligent Image Search Results Summarization and Browsing
    6.
    发明申请
    Intelligent Image Search Results Summarization and Browsing 有权
    智能图像搜索结果汇总和浏览

    公开(公告)号:US20110194761A1

    公开(公告)日:2011-08-11

    申请号:US12701969

    申请日:2010-02-08

    IPC分类号: G06K9/00 G06K9/62 G09G5/00

    摘要: Techniques for intelligent image search results summarization and browsing scheme are described. Images having visual attributes are evaluated for similarities based in part on their visual attributes. At least one preference score indicating a probability of an image to be selected into a summary is calculated for each image. Images are selected based on the similarity of the selected images to the other images and the preference scores of the selected images. A summary of the plurality of images is generated including the selected one individual image.

    摘要翻译: 描述了智能图像搜索结果汇总和浏览方案的技术。 根据其视觉属性,对具有视觉属性的图像进行相似度的评估。 针对每个图像计算指示将图像选择为概要的概率的至少一个偏好分数。 基于所选择的图像与其他图像的相似度以及所选图像的偏好分数来选择图像。 生成包括所选择的一个单独图像的多个图像的概要。

    Intelligent Image Search Results Summarization and Browsing
    7.
    发明申请
    Intelligent Image Search Results Summarization and Browsing 审中-公开
    智能图像搜索结果汇总和浏览

    公开(公告)号:US20140321761A1

    公开(公告)日:2014-10-30

    申请号:US14324375

    申请日:2014-07-07

    IPC分类号: G06F17/30 G06K9/62

    摘要: Techniques for intelligent image search results summarization and browsing scheme are described. Images having visual attributes are evaluated for similarities based in part on their visual attributes. At least one preference score indicating a probability of an image to be selected into a summary is calculated for each image. Images are selected based on the similarity of the selected images to the other images and the preference scores of the selected images. A summary of the plurality of images is generated including the selected one individual image.

    摘要翻译: 描述了智能图像搜索结果汇总和浏览方案的技术。 根据其视觉属性,对具有视觉属性的图像进行相似度的评估。 针对每个图像计算指示将图像选择为概要的概率的至少一个偏好分数。 基于所选择的图像与其他图像的相似度以及所选图像的偏好分数来选择图像。 生成包括所选择的一个单独图像的多个图像的概要。

    Concept-structured image search
    8.
    发明授权
    Concept-structured image search 有权
    概念结构图像搜索

    公开(公告)号:US08392430B2

    公开(公告)日:2013-03-05

    申请号:US12565313

    申请日:2009-09-23

    IPC分类号: G06F17/30

    CPC分类号: G06F17/3053 G06F17/30265

    摘要: The concept-structured image search technique described herein pertains to a technique for enabling a user to indicate their semantic intention and then retrieve and rank images from a database or other image set according to this intention. The concept-structured image search technique described herein includes a new interface for image search. With this interface, a user can freely type several key textual words in arbitrary positions on a blank image, and also describe a region for each keyword that indicates its influence scope, which is called concept structure herein. The concept-structured image search technique will return and rank images that are in accordance with the concept structure indicated by the user. One embodiment of the technique can be used to create a synthesized image without actually using the synthesized image to perform a search of an image set.

    摘要翻译: 本文描述的概念结构图像搜索技术涉及一种使用户能够指示其语义意图,然后根据该意图从数据库或其他图像集中检索和排列图像的技术。 本文所述的概念结构图像搜索技术包括用于图像搜索的新界面。 通过该接口,用户可以在空白图像上任意位置自由地键入几个关键文本字,并且还描述指示其影响范围的每个关键字的区域,这在本文中被称为概念结构。 概念结构图像搜索技术将返回并对与用户指示的概念结构相一致的图像进行排序。 该技术的一个实施例可以用于创建合成图像而不实际使用合成图像来执行图像集的搜索。

    Hybrid neighborhood graph search for scalable visual indexing
    9.
    发明授权
    Hybrid neighborhood graph search for scalable visual indexing 有权
    混合邻域图搜索可缩放的视觉索引

    公开(公告)号:US08370363B2

    公开(公告)日:2013-02-05

    申请号:US13091323

    申请日:2011-04-21

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30979

    摘要: A hybrid search method may be used to identify information responsive to a query. A search may be performed utilizing a neighborhood graph and a partitioning tree. The partitioning tree may be searched to select one or more pivots that may be used to guide a subsequent search in the neighborhood graph. Once the search in the neighborhood graph is unable to identify nearest neighbors in closer proximity to the query, the search may be switched to the partitioning tree. The partitioning tree may then be searched to select pivots that may be used to guide subsequent searches in the neighborhood graph. The searches performed in the partitioning tree and/or the neighborhood graph may be conducted utilizing an iterative algorithm.

    摘要翻译: 可以使用混合搜索方法来识别响应于查询的信息。 可以使用邻域图和分区树来执行搜索。 可以搜索分区树以选择可用于指导邻域图中的后续搜索的一个或多个枢轴。 一旦邻域图中的搜索无法识别更靠近查询的最近邻居,则可以将搜索切换到分区树。 然后可以搜索分区树以选择可用于指导邻域图中的后续搜索的枢轴。 可以使用迭代算法来执行在分区树和/或邻域图中执行的搜索。

    HYBRID NEIGHBORHOOD GRAPH SEARCH FOR SCALABLE VISUAL INDEXING

    公开(公告)号:US20120271833A1

    公开(公告)日:2012-10-25

    申请号:US13091323

    申请日:2011-04-21

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30979

    摘要: A hybrid search method may be used to identify information responsive to a query. A search may be performed utilizing a neighborhood graph and a partitioning tree. The partitioning tree may be searched to select one or more pivots that may be used to guide a subsequent search in the neighborhood graph. Once the search in the neighborhood graph is unable to identify nearest neighbors in closer proximity to the query, the search may be switched to the partitioning tree. The partitioning tree may then be searched to select pivots that may be used to guide subsequent searches in the neighborhood graph. The searches performed in the partitioning tree and/or the neighborhood graph may be conducted utilizing an iterative algorithm.

    摘要翻译: 可以使用混合搜索方法来识别响应于查询的信息。 可以使用邻域图和分区树来执行搜索。 可以搜索分区树以选择可用于指导邻域图中的后续搜索的一个或多个枢轴。 一旦邻域图中的搜索无法识别更靠近查询的最近邻居,则可以将搜索切换到分区树。 然后可以搜索分区树以选择可用于指导邻域图中的后续搜索的枢轴。 可以使用迭代算法来执行在分区树和/或邻域图中执行的搜索。