Media fingerprinting and identification system

    公开(公告)号:US10423654B2

    公开(公告)日:2019-09-24

    申请号:US16355727

    申请日:2019-03-16

    Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

    Distributed and tiered architecture for content search and content monitoring

    公开(公告)号:US09436689B2

    公开(公告)日:2016-09-06

    申请号:US14990565

    申请日:2016-01-07

    Abstract: An efficient large scale search system for video and multi-media content using a distributed database and search, and tiered search servers is described. Selected content is stored at the distributed local database and tier1 search server(s). Content matching frequent queries, and frequent unidentified queries are cached at various levels in the search system. Content is classified using feature descriptors and geographical aspects, at feature level and in time segments. Queries not identified at clients and tier1 search server(s) are queried against tier2 or lower search server(s). Search servers use classification and geographical partitioning to reduce search cost. Methods for content tracking and local content searching are executed on clients. The client performs local search, monitoring and/or tracking of the query content with the reference content and local search with a database of reference fingerprints. This shifts the content search workload from central servers to the distributed monitoring clients.

    Distributed and Tiered Architecture for Content Search and Content Monitoring

    公开(公告)号:US20160371269A1

    公开(公告)日:2016-12-22

    申请号:US15163004

    申请日:2016-05-24

    Abstract: An efficient large scale search system for video and multi-media content using a distributed database and search, and tiered search servers is described. Selected content is stored at the distributed local database and tier1 search server(s). Content matching frequent queries, and frequent unidentified queries are cached at various levels in the search system. Content is classified using feature descriptors and geographical aspects, at feature level and in time segments. Queries not identified at clients and tier1 search server(s) are queried against tier2 or lower search server(s). Search servers use classification and geographical partitioning to reduce search cost. Methods for content tracking and local content searching are executed on clients. The client performs local search, monitoring and/or tracking of the query content with the reference content and local search with a database of reference fingerprints. This shifts the content search workload from central servers to the distributed monitoring clients.

    DISTRIBUTED AND TIERED ARCHITECTURE FOR CONTENT SEARCH AND CONTENT MONITORING
    8.
    发明申请
    DISTRIBUTED AND TIERED ARCHITECTURE FOR CONTENT SEARCH AND CONTENT MONITORING 有权
    内容搜索和内容监控的分布式和分层结构

    公开(公告)号:US20160132500A1

    公开(公告)日:2016-05-12

    申请号:US14990565

    申请日:2016-01-07

    Abstract: An efficient large scale search system for video and multi-media content using a distributed database and search, and tiered search servers is described. Selected content is stored at the distributed local database and tier1 search server(s). Content matching frequent queries, and frequent unidentified queries are cached at various levels in the search system. Content is classified using feature descriptors and geographical aspects, at feature level and in time segments. Queries not identified at clients and tier1 search server(s) are queried against tier2 or lower search server(s). Search servers use classification and geographical partitioning to reduce search cost. Methods for content tracking and local content searching are executed on clients. The client performs local search, monitoring and/or tracking of the query content with the reference content and local search with a database of reference fingerprints. This shifts the content search workload from central servers to the distributed monitoring clients.

    Abstract translation: 描述了使用分布式数据库和搜索以及分层搜索服务器的视频和多媒体内容的高效大规模搜索系统。 所选内容存储在分布式本地数据库和tier1搜索服务器上。 内容匹配频繁查询和频繁的不明查询在搜索系统的各个级别进行缓存。 内容使用特征描述符和地理方面,在特征级别和时间段中进行分类。 在客户端和tier1搜索服务器上未识别的查询被查询到tier2或更低的搜索服务器。 搜索服务器使用分类和地理分区来降低搜索成本。 在客户端执行内容跟踪和本地内容搜索的方法。 客户端用参考内容和具有参考指纹数据库的本地搜索来执行查询内容的本地搜索,监视和/或跟踪。 这将内容搜索工作负载从中央服务器转移到分布式监控客户端。

    Media fingerprinting and identification system

    公开(公告)号:US10387482B1

    公开(公告)日:2019-08-20

    申请号:US16388747

    申请日:2019-04-18

    Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

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