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:
Jan. 05, 2021

Filed:

Jul. 12, 2017
Applicant:

Nio Usa, Inc., San Jose, CA (US);

Inventors:

Vidya Elangovan, Cupertino, CA (US);

Prashant Jain, San Jose, CA (US);

Anthony Tao Liang, Palo Alto, CA (US);

Guan Wang, San Jose, CA (US);

Assignee:

NIO USA, Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 19/00 (2011.01); G06T 17/10 (2006.01); G06K 9/66 (2006.01); G06T 19/20 (2011.01); H04N 7/18 (2006.01); G06T 7/70 (2017.01); G06F 3/03 (2006.01); G06K 9/00 (2006.01); G06F 3/01 (2006.01); G06F 9/451 (2018.01);
U.S. Cl.
CPC ...
G06T 19/006 (2013.01); G06F 3/011 (2013.01); G06F 3/0304 (2013.01); G06F 9/453 (2018.02); G06K 9/00664 (2013.01); G06K 9/00671 (2013.01); G06K 9/66 (2013.01); G06T 7/70 (2017.01); G06T 17/10 (2013.01); G06T 19/20 (2013.01); H04N 7/183 (2013.01); G06T 2207/30244 (2013.01); G06T 2207/30248 (2013.01);
Abstract

Embodiments of the present disclosure are directed to an augmented reality based user's manual for a vehicle implemented as an application on a mobile device which allows the user to point a mobile phone, tablet or an augmented reality headset at any part of the vehicle interior or exterior and experience augmented annotations, overlays, popups, etc. displayed on images of real parts of the car captured by the user's mobile device. Embodiments provide for estimating the camera pose in six degrees of freedom based on the content of the captured image or video and using a neural network trained on a dense sampling of a three-dimensional model of the car rendered with realistic textures to identify and properly align the augmented reality presentation with the image of the vehicle being captured by the mobile device.


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