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1. 发明授权

US08370363B2 Hybrid neighborhood graph search for scalable visual indexing 有权
标题翻译：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
申请人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , Jing Wang
发明人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , Jing Wang
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。

2. 发明申请

US20120271833A1 HYBRID NEIGHBORHOOD GRAPH SEARCH FOR SCALABLE VISUAL INDEXING 有权
公开(公告)号：US20120271833A1
公开(公告)日：2012-10-25
申请号：US13091323
申请日：2011-04-21
申请人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , Jing Wang
发明人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , Jing Wang
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。

3. 发明授权

US08705870B2 Image searching by approximate κ-NN graph 有权
标题翻译：图像搜索近似＆kgr; -NN图
公开(公告)号：US08705870B2
公开(公告)日：2014-04-22
申请号：US13411213
申请日：2012-03-02
申请人： Jingdong Wang , Shipeng Li , Jing Wang
发明人： Jingdong Wang , Shipeng Li , Jing Wang
IPC分类号： G06K9/50 , G06K9/34 , G06K9/54
CPC分类号： G06F17/30247
摘要： This disclosure describes techniques for searching for similar images to an image query by using an approximate k-Nearest Neighbor (k-NN) graph. The approximate k-NN graph is constructed from data points partitioned into subsets to further identify nearest-neighboring data points for each data point. The data points may connect with the nearest-neighboring data points in a subset to form an approximate neighborhood subgraph. These subgraphs from all the subsets are combined together to form a base approximate k-NN graph. Then by performing more random hierarchical partition, more base approximate k-NN graphs are formed, and further combined together to create an approximate k-NN graph. The approximate k-NN graph expands into other neighborhoods and identifies the best k-NN data points. The approximate k-NN graph retrieves the best NN data points, based at least in part on the retrieved best k-NN data points representing images being similar in appearance to the image query.
摘要翻译：本公开描述了通过使用近似k最近邻（k-NN）图来搜索图像查询的类似图像的技术。从划分成子集的数据点构建近似k-NN图，以进一步识别每个数据点的最近邻数据点。数据点可以与子集中的最邻近的数据点连接，以形成大致的邻域子图。来自所有子集的这些子图被组合在一起以形成基本的近似k-NN图。然后通过执行更多的随机分层分区，形成更多的基本近似k-NN图，并进一步组合在一起以创建一个近似的k-NN图。近似的k-NN图扩展到其他邻域，并识别最佳的k-NN数据点。至少部分地基于检索出的最佳k-NN数据点，近似k-NN图形检索出最佳的NN数据点，该数据点表示与图像查询相似的图像。

4. 发明申请

US20130230255A1 Image Searching By Approximate k-NN Graph 有权
标题翻译：通过近似k-NN图进行图像搜索
公开(公告)号：US20130230255A1
公开(公告)日：2013-09-05
申请号：US13411213
申请日：2012-03-02
申请人： Jingdong Wang , Shipeng Li , Jing Wang
发明人： Jingdong Wang , Shipeng Li , Jing Wang
IPC分类号： G06K9/46
CPC分类号： G06F17/30247
摘要： This disclosure describes techniques for searching for similar images to an image query by using an approximate k-Nearest Neighbor (k-NN) graph. The approximate k-NN graph is constructed from data points partitioned into subsets to further identify nearest-neighboring data points for each data point. The data points may connect with the nearest-neighboring data points in a subset to form an approximate neighborhood subgraph. These subgraphs from all the subsets are combined together to form a base approximate k-NN graph. Then by performing more random hierarchical partition, more base approximate k-NN graphs are formed, and further combined together to create an approximate k-NN graph. The approximate k-NN graph expands into other neighborhoods and identifies the best k-NN data points. The approximate k-NN graph retrieves the best NN data points, based at least in part on the retrieved best k-NN data points representing images being similar in appearance to the image query.
摘要翻译：本公开描述了通过使用近似k最近邻（k-NN）图来搜索图像查询的类似图像的技术。从划分成子集的数据点构建近似k-NN图，以进一步识别每个数据点的最近邻数据点。数据点可以与子集中的最邻近的数据点连接，以形成大致的邻域子图。来自所有子集的这些子图被组合在一起以形成基本的近似k-NN图。然后通过执行更多的随机分层分区，形成更多的基本近似k-NN图，并进一步组合在一起以创建一个近似的k-NN图。近似的k-NN图扩展到其他邻域，并识别最佳的k-NN数据点。至少部分地基于检索出的最佳k-NN数据点，近似k-NN图形检索出最佳的NN数据点，该数据点表示与图像查询相似的图像。

5. 发明申请

US20100158412A1 INTERACTIVELY RANKING IMAGE SEARCH RESULTS USING COLOR LAYOUT RELEVANCE 有权
标题翻译：使用彩色布局相关的互动排名图像搜索结果
公开(公告)号：US20100158412A1
公开(公告)日：2010-06-24
申请号：US12341953
申请日：2008-12-22
申请人： Jingdong Wang , Shipeng Li , Xian Sheng Hua , Yinghai Zhao
发明人： Jingdong Wang , Shipeng Li , Xian Sheng Hua , Yinghai Zhao
IPC分类号： G06K9/54 , G06F17/30
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。

6. 发明授权

US09092673B2 Computing visual and textual summaries for tagged image collections 有权
标题翻译：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
申请人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , Hao Xu
发明人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , Hao Xu
IPC分类号： G06K9/62 , G06K9/00 , G06F17/30
CPC分类号： G06K9/00664 , G06F17/30265 , G06F17/30719 , G06K9/6255
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。

7. 发明授权

US08712991B2 Document-related representative information 有权
标题翻译：文件相关的代表信息
公开(公告)号：US08712991B2
公开(公告)日：2014-04-29
申请号：US13178034
申请日：2011-07-07
申请人： Jingdong Wang , Shipeng Li
发明人： Jingdong Wang , Shipeng Li
IPC分类号： G06F17/30
CPC分类号： G06F17/3064
摘要： Some implementations include techniques and arrangements to provide document-related representative information with search results. For example, a representative query and/or representative results may be provided for one or more individual documents identified in a set of search results to supplement the search results returned in response to a received search query. The representative queries may be determined by correlating a plurality of previously submitted queries in search log data with a plurality of documents returned in response to the queries. In some implementations, click-through frequency for a particular document with respect to the plurality of queries may be taken into consideration when determining the representative queries for the particular document. In some implementations, the representative queries serve to categorize the search results based on subject matter, and a link may be provided to representative results corresponding to the representative query for accessing documents directed to similar subject matter.
摘要翻译：一些实现包括用于向搜索结果提供与文档相关的代表性信息的技术和布置。例如，可以为在一组搜索结果中标识的一个或多个单独文档提供代表性查询和/或代表性结果，以补充响应于所接收的搜索查询返回的搜索结果。可以通过将搜索日志数据中的多个先前提交的查询与响应于查询返回的多个文档相关联来确定代表性查询。在一些实现中，当确定特定文档的代表性查询时，可以考虑针对多个查询的特定文档的点击频率。在一些实现中，代表性查询用于基于主题对搜索结果进行分类，并且可以向链接提供对应于代表性查询的代表性结果，用于访问针对相似主题的文档。

8. 发明授权

US08645380B2 Optimized KD-tree for scalable search 有权
标题翻译：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
申请人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , You Jia
发明人： Jingdong Wang , Xian-Sheng Hua , Shipeng Li , You Jia
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。

9. 发明申请

US20130223740A1 Salient Object Segmentation 有权
标题翻译：显着对象分割
公开(公告)号：US20130223740A1
公开(公告)日：2013-08-29
申请号：US13403747
申请日：2012-02-23
申请人： Jingdong Wang , Shipeng Li , Huaizu Jiang
发明人： Jingdong Wang , Shipeng Li , Huaizu Jiang
IPC分类号： G06K9/34
CPC分类号： G06K9/4638 , G06T7/12 , G06T7/143 , G06T2207/10024 , G06T2207/20016
摘要： Techniques for identifying a salient object with respect to its context are described. A process receives an input image that includes a salient object. The process segments the input image into multiple regions and calculates a saliency value for each of the segmented regions based on scale image levels. The process constructs saliency maps based at least in part on the calculated saliency value, and combines the saliency maps to construct a total saliency map. Next, the process connects a set of line segments computed from the input image and utilizes the total saliency map to compute a closed boundary, which forms a shape prior from the closed boundary, and extracts the salient object from the total saliency map and the shape prior.
摘要翻译：描述了相对于其上下文识别显着对象的技术。进程接收包含突出对象的输入图像。该过程将输入图像分割成多个区域，并且基于比例图像级别计算每个分割区域的显着性值。该过程至少部分地基于计算的显着值构建显着图，并结合显着图以构建总显着图。接下来，该过程连接从输入图像计算的一组线段，并利用总显示图来计算闭合边界，该闭合边界形成从封闭边界之前的形状，并从总显着图和形状中提取显着对象之前

10. 发明授权

US08406573B2 Interactively ranking image search results using color layout relevance 有权
标题翻译：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
申请人： Jingdong Wang , Shipeng Li , Xian-Sheng Hua , Yinghai Zhao
发明人： Jingdong Wang , Shipeng Li , Xian-Sheng Hua , Yinghai Zhao
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。

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