Invention Grant
- Patent Title: Mixing segmentation algorithms utilizing soft classifications to identify segments of three-dimensional digital models
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Application No.: US16907663Application Date: 2020-06-22
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Publication No.: US11315255B2Publication Date: 2022-04-26
- Inventor: Vladimir Kim , Aaron Hertzmann , Mehmet Yumer
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Keller Preece PLLC
- Main IPC: G06T7/143
- IPC: G06T7/143 ; G06K9/68 ; G06K9/34 ; G06K9/00 ; G06T7/11

Abstract:
The present disclosure includes methods and systems for identifying and manipulating a segment of a three-dimensional digital model based on soft classification of the three-dimensional digital model. In particular, one or more embodiments of the disclosed systems and methods identify a soft classification of a digital model and utilize the soft classification to tune segmentation algorithms. For example, the disclosed systems and methods can utilize a soft classification to select a segmentation algorithm from a plurality of segmentation algorithms, to combine segmentation parameters from a plurality of segmentation algorithms, and/or to identify input parameters for a segmentation algorithm. The disclosed systems and methods can utilize the tuned segmentation algorithms to accurately and efficiently identify a segment of a three-dimensional digital model.
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