- Patent Title: Determining depth from structured light using trained classifiers
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Application No.: US15071133Application Date: 2016-03-15
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Publication No.: US09916524B2Publication Date: 2018-03-13
- Inventor: Sean Ryan Francesco Fanello , Christoph Rhemann , Adarsh Prakash Murthy Kowdle , Vladimir Tankovich , David Kim , Shahram Izadi
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Drinker Biddle & Reath LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G06T7/00 ; G06T7/521

Abstract:
Techniques for determining depth for a visual content item using machine-learning classifiers include obtaining a visual content item of a reference light pattern projected onto an object, and determining shifts in locations of pixels relative to other pixels representing the reference light pattern. Disparity, and thus depth, for pixels may be determined by executing one or more classifiers trained to identify disparity for pixels based on the shifts in locations of the pixels relative to other pixels of a visual content item depicting in the reference light pattern. Disparity for pixels may be determined using a visual content item of a reference light pattern projected onto an object without having to match pixels between two visual content items, such as a reference light pattern and a captured visual content item.
Public/Granted literature
- US20170236286A1 Determining Depth from Structured Light Using Trained Classifiers Public/Granted day:2017-08-17
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