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:
Jul. 11, 2023

Filed:

Dec. 02, 2019
Applicant:

Korea Advanced Institute of Science and Technology, Daejeon, KR;

Inventors:

YongMan Ro, Daejeon, KR;

Hak Gu Kim, Daejeon, KR;

Sangmin Lee, Daejeon, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06T 19/00 (2011.01); G09B 3/06 (2006.01); G06V 20/20 (2022.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06V 10/82 (2022.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06T 19/006 (2013.01); G06V 10/454 (2022.01); G06V 10/82 (2022.01); G06V 20/20 (2022.01); G09B 3/06 (2013.01);
Abstract

A virtual reality (VR) sickness assessment method according to an embodiment includes receiving virtual reality content, and quantitatively evaluating virtual reality sickness for the received virtual reality content using a neural network based on a pre-trained neural mismatch model. The evaluating of the virtual reality sickness may include predicting an expected visual signal for an input visual signal of the virtual reality content based on the neural mismatch model, extracting a neural mismatch feature between the predicted expected visual signal based on the neural mismatch model and an input visual signal for a corresponding frame of the virtual reality content corresponding to the expected visual signal, and evaluating a level of the virtual reality sickness based on the neural mismatch model and the extracted neural mismatch feature.


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