Invention Grant
- Patent Title: Object retrieval and localization using a spatially-constrained similarity model
- Patent Title (中): 使用空间约束相似性模型的对象检索和定位
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Application No.: US13552595Application Date: 2012-07-18
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Publication No.: US08874557B2Publication Date: 2014-10-28
- Inventor: Zhe Lin , Jonathan W. Brandt , Xiaohui Shen
- Applicant: Zhe Lin , Jonathan W. Brandt , Xiaohui Shen
- Applicant Address: US CA San Jose
- Assignee: Adobe Systems Incorporated
- Current Assignee: Adobe Systems Incorporated
- Current Assignee Address: US CA San Jose
- Agency: Wolfe-SBMC
- Main IPC: G06F17/30
- IPC: G06F17/30 ; G06F7/00 ; G06K9/46 ; G06K9/62 ; G06Q30/02

Abstract:
Methods, apparatus, and computer-readable storage media for object retrieval and localization that employ a spatially-constrained similarity model. A spatially-constrained similarity measure may be evaluated by a voting-based scoring technique. Object retrieval and localization may thus be achieved without post-processing. The spatially-constrained similarity measure may handle object rotation, scaling and view point change. The similarity measure can be efficiently calculated by the voting-based method and integrated with inverted files. The voting-based scoring technique may simultaneously retrieve and localize a query object in a collection of images such as an image database. The object retrieval and localization technique may, for example, be implemented with a k-nearest neighbor (k-NN) re-ranking method in or as a retrieval method, system or module. The k-NN re-ranking method may be applied to improve query results of the object retrieval and localization technique.
Public/Granted literature
- US20130060765A1 OBJECT RETRIEVAL AND LOCALIZATION USING A SPATIALLY-CONSTRAINED SIMILARITY MODEL Public/Granted day:2013-03-07
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