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:
Sep. 20, 2022

Filed:

May. 12, 2022
Applicant:

Tsinghua University, Beijing, CN;

Inventors:

Lu Fang, Beijing, CN;

Zhihao Xu, Beijing, CN;

Xiaoyun Yuan, Beijing, CN;

Tiankuang Zhou, Beijing, CN;

Qionghai Dai, Beijing, CN;

Assignee:

TSINGHUA UNIVERSITY, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/557 (2017.01); H04N 13/128 (2018.01); G06N 3/04 (2006.01); H04N 13/00 (2018.01); H04N 13/239 (2018.01); H04N 13/271 (2018.01); G06T 7/593 (2017.01); G02B 27/14 (2006.01);
U.S. Cl.
CPC ...
G06T 7/557 (2017.01); G02B 27/14 (2013.01); G06N 3/04 (2013.01); G06T 7/593 (2017.01); H04N 13/128 (2018.05); H04N 13/239 (2018.05); H04N 13/271 (2018.05); G06T 2207/10012 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20228 (2013.01); H04N 2013/0081 (2013.01);
Abstract

A method for intelligent light field depth classification based on optoelectronic computing includes capturing and identifying binocular images of a scene within a depth range through a pair of binocular cameras; mapping each depth value in the depth range to a disparity value between the binocular images, to obtain a disparity range of the scene within the depth range; labeling training data based on the disparity range to obtain a pre-trained diffraction neural network model; loading a respective weight for each layer of a network obtained after training into a corresponding optical element based on the pre-trained diffraction neural network model; and after the respective weight for each layer of the network is loaded, performing forward propagation inference on new input data of the scene, and outputting a depth classification result corresponding to each pixel in the binocular images of the scene.


Find Patent Forward Citations

Loading…