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    • 3. 发明授权
    • Content collection search with robust content matching
    • 内容集合搜索与强大的内容匹配
    • US08943090B2
    • 2015-01-27
    • US13621171
    • 2012-09-15
    • Arnab S. DhuaSunil RameshMax DelgadilloRaghavan Manmatha
    • Arnab S. DhuaSunil RameshMax DelgadilloRaghavan Manmatha
    • G06F17/30G06K9/46G06K9/62
    • G06F17/30256G06F17/30247G06F17/30259G06F17/30542G06F17/30867G06K9/46G06K9/6203
    • Systems and approaches for searching a content collection corresponding to query content are provided. In particular, false positive match rates between the query content and the content collection may be reduced with a minimum content region test and/or a minimum features per scale test. For example, by correlating content descriptors of a content piece in the content collection with query descriptors of the query content, the content piece can be determined to match the query content when a particular region of the content piece and/or a particular region of a query descriptor have a proportionate size meeting or exceeding a specified minimum. Alternatively, or in addition, the false positive match rate between query content and a content piece can be reduced by comparing content descriptors and query descriptors of features at a plurality of scales. A content piece can be determined to match the query content according to descriptor proportion quotas for the plurality of scales.
    • 提供了用于搜索与查询内容相对应的内容集合的系统和方法。 特别地,可以通过最小内容区域测试和/或每个比例测试的最小特征来减少查询内容和内容收集之间的假阳性匹配率。 例如,通过将内容集合中的内容片段的内容描述符与查询内容的查询描述符相关联,可以确定内容片段与内容片段的特定区域和/或内容片段的特定区域 查询描述符的比例大小满足或超过规定的最小值。 或者或另外,通过比较多个尺度的特征的内容描述符和查询描述符,可以减少查询内容与内容片段之间的假正匹配率。 可以根据多个尺度的描述符比例配额来确定内容片段以匹配查询内容。
    • 8. 发明授权
    • Determining similarity using human generated data
    • 使用人造数据确定相似度
    • US09104701B1
    • 2015-08-11
    • US13482717
    • 2012-05-29
    • Michael Q. PhungArnab S. DhuaKetan R. DeshpandeSunil Ramesh
    • Michael Q. PhungArnab S. DhuaKetan R. DeshpandeSunil Ramesh
    • G06K9/68G06F17/30
    • G06F17/30256G06F17/30047G06F17/3005G06F17/30277
    • Subjective user-generated data can be utilized to determine visually similar items. Various item descriptors can be determined for a pair of items, which can provide an objective measure of visual aspects of those items, such as how similar those items are in color, style, material, or texture. The ways in which users interact with data for those items, either explicitly or implicitly through user behavior, can provide a level of perceived visual similarity on behalf of these users. The perceived, subjective visual similarity data from the users can be used to adjust a weighting of the various item descriptor factors for a pair of items, or otherwise adjust a visual similarity score, such that items selected as being visually similar more accurately reflect the subjective opinions of the users.
    • 主观用户生成的数据可用于确定视觉上相似的项目。 可以为一对项目确定各种项目描述符,这些项目可以提供这些项目的视觉方面的客观测量,诸如这些项目在颜色,样式,材料或纹理中的相似度。 用户通过用户行为明确或隐含地与这些项目的数据进行交互的方式可以代表这些用户提供一定程度的感知视觉相似度。 可以使用来自用户的感知的,主观的视觉相似性数据来调整一对项目的各种项目描述符因子的加权,或者另外调整视觉相似性得分,使得被选择为视觉上类似的项目更准确地反映主观 用户意见。
    • 9. 发明授权
    • Content search with category-aware visual similarity
    • 内容搜索与类别感知视觉相似性
    • US08990199B1
    • 2015-03-24
    • US12895601
    • 2010-09-30
    • Sunil RameshArnab S. DhuaSupratik BhattacharyyaGurumurthy D. RamkumarGautam Bhargava
    • Sunil RameshArnab S. DhuaSupratik BhattacharyyaGurumurthy D. RamkumarGautam Bhargava
    • G06F7/00G06F17/30
    • G06F17/30259G06F17/30256G06F17/30864
    • Visual incongruity in search result sets may be reduced at least in part by searching an optimized visually significant subset of a category tree that categorizes a collection of content. The category tree may be optimized at build time at least in part by pruning with respect to visual coherence and by the size of the content collection subset referenced by particular categories. Content collection subset sizes both too large and too small can detract from the visual significance of a particular category. The visually significant subset of the category tree may be further optimized at query time by intersecting the visually significant subset with the query-associated sub-tree(s) and further pruning categories in the visually significant subset that have child categories in the visually significant subset. Searching with respect to the optimized visually significant subset can also improve search efficiency.
    • 搜索结果集中的视觉不协调可以至少部分地通过搜索对内容集合进行分类的类别树的优化的视觉上重要的子集来减少。 类别树可以在构建时间至少部分地通过针对视觉一致性的修剪以及由特定类别引用的内容收集子集的大小进行优化。 内容收集子集大小太大和太小可能会降低特定类别的视觉含义。 可以在查询时间通过将视觉上有意义的子集与查询关联的子树相交并在视觉上有意义的子集中进一步修剪在视觉上有意义的子集中具有子类别的视觉上重要子集中的类别,来进一步优化类别树的视觉上重要的子集 。 关于优化的视觉显着子集的搜索也可以提高搜索效率。