The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 24, 2018

Filed:

Sep. 03, 2015
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Jeffrey Jesus Evertt, Kirkland, WA (US);

Justin Avram Clark, Kirkland, WA (US);

Christopher Harley Willoughby, Kenmore, WA (US);

Mike Scavezze, Bellevue, WA (US);

Joel Deaguero, Snohomish, WA (US);

Relja Markovic, Seattle, WA (US);

Joe Sola, Seattle, WA (US);

David Haley, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 13/02 (2006.01); G06K 9/66 (2006.01); G06T 7/00 (2017.01); H04N 5/222 (2006.01); G06T 19/20 (2011.01); A63F 13/213 (2014.01); A63F 13/53 (2014.01); G06T 15/08 (2011.01); G06T 7/70 (2017.01); G06T 7/50 (2017.01); G06T 7/12 (2017.01);
U.S. Cl.
CPC ...
G06T 7/0051 (2013.01); A63F 13/213 (2014.09); A63F 13/53 (2014.09); G06T 7/12 (2017.01); G06T 7/50 (2017.01); G06T 7/70 (2017.01); G06T 15/08 (2013.01); G06T 19/20 (2013.01); H04N 5/2226 (2013.01); H04N 13/0257 (2013.01); H04N 13/0271 (2013.01); A63F 2300/1093 (2013.01); A63F 2300/6018 (2013.01); G06T 2200/08 (2013.01); G06T 2207/10004 (2013.01); G06T 2207/10028 (2013.01); G06T 2219/2012 (2013.01);
Abstract

Digitizing objects in a picture is discussed herein. A user presents the object to a camera, which captures the image comprising color and depth data for the front and back of the object. For both front and back images, the closest point to the camera is determined by analyzing the depth data. From the closest points, edges of the object are found by noting large differences in depth data. The depth data is also used to construct point cloud constructions of the front and back of the object. Various techniques are applied to extrapolate edges, remove seams, extend color intelligently, filter noise, apply skeletal structure to the object, and optimize the digitization further. Eventually, a digital representation is presented to the user and potentially used in different applications (e.g., games, Web, etc.).


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