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. 21, 2025

Filed:

Sep. 04, 2023
Applicant:

Hangzhou Dianzi University, Hangzhou, CN;

Inventors:

Gangyong Jia, Hangzhou, CN;

Yumiao Zhao, Hangzhou, CN;

Huanle Rao, Hangzhou, CN;

Ziwei Song, Hangzhou, CN;

Minghui Yu, Hangzhou, CN;

Hong Xu, Hangzhou, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 3/042 (2005.12); G06V 10/77 (2021.12); G06V 10/774 (2021.12); G06V 10/80 (2021.12); G06V 10/82 (2021.12); G06V 20/40 (2021.12); G06V 40/20 (2021.12);
U.S. Cl.
CPC ...
G06F 3/0425 (2012.12); G06V 10/7715 (2021.12); G06V 10/774 (2021.12); G06V 10/806 (2021.12); G06V 10/82 (2021.12); G06V 20/46 (2021.12); G06V 40/28 (2021.12);
Abstract

Disclosed is a method and system for predicting a touch interaction position on a large display based on a binocular camera. The method includes: separately acquiring arm movement video frames of a user and facial and eye movement video frames of the user by a binocular camera; extracting a video clip of each tapping action from the arm movement video frames and the facial and eye movement video frames and obtaining a key frame by screening; marking the key frame of each tapping action with coordinates to indicate coordinates of a finger in a display screen; inputting the marked key frame to an efficient convolutional network for online video understanding (ECO)-Lite neural network for training to obtain a predictive network model; and inputting a video frame of a current operation to be predicted to the predictive network model and outputting a touch interaction position predicted for the current operation.


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