Invention Grant
US09443314B1 Hierarchical conditional random field model for labeling and segmenting images
有权
用于标记和分割图像的分层条件随机场模型
- Patent Title: Hierarchical conditional random field model for labeling and segmenting images
- Patent Title (中): 用于标记和分割图像的分层条件随机场模型
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Application No.: US13434515Application Date: 2012-03-29
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Publication No.: US09443314B1Publication Date: 2016-09-13
- Inventor: Qixing Huang , Mei Han , Bo Wu , Sergey Ioffe
- Applicant: Qixing Huang , Mei Han , Bo Wu , Sergey Ioffe
- Applicant Address: US CA Mountain View
- Assignee: Google Inc.
- Current Assignee: Google Inc.
- Current Assignee Address: US CA Mountain View
- Agency: Lerner, David, Littenberg, Krumholz & Mentlik, LLP
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/00 ; G06K9/00

Abstract:
An image processing system automatically segments and labels an image using a hierarchical classification model. A global classification model determines initial labels for an image based on features of the image. A label-based descriptor is generated based on the initial labels. A local classification model is then selected from a plurality of learned local classification model based on the label-based descriptor. The local classification model is applied to the features of the input image to determined refined labels. The refined labels are stored in association with the input image.
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