Invention Grant
US09436893B2 Distributed similarity learning for high-dimensional image features
有权
分布式相似度学习用于高维图像特征
- Patent Title: Distributed similarity learning for high-dimensional image features
- Patent Title (中): 分布式相似度学习用于高维图像特征
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Application No.: US14091972Application Date: 2013-11-27
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Publication No.: US09436893B2Publication Date: 2016-09-06
- Inventor: Jianchao Yang , Zhaowen Wang , Zhe Lin , Jonathan Brandt
- Applicant: Adobe Systems Incorporated
- Applicant Address: US CA San Jose
- Assignee: ADOBE SYSTEMS INCORPORATED
- Current Assignee: ADOBE SYSTEMS INCORPORATED
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon LLP
- Main IPC: G06K9/62
- IPC: G06K9/62
Abstract:
A system and method for distributed similarity learning for high-dimensional image features are described. A set of data features is accessed. Subspaces from a space formed by the set of data features are determined using a set of projection matrices. Each subspace has a dimension lower than a dimension of the set of data features. Similarity functions are computed for the subspaces. Each similarity function is based on the dimension of the corresponding subspace. A linear combination of the similarity functions is performed to determine a similarity function for the set of data features.
Public/Granted literature
- US20150146973A1 DISTRIBUTED SIMILARITY LEARNING FOR HIGH-DIMENSIONAL IMAGE FEATURES Public/Granted day:2015-05-28
Information query
