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:
Oct. 24, 2023

Filed:

Mar. 09, 2021
Applicant:

Lego A/s, Billund, DK;

Inventors:

Marko Velic, Zagreb, HR;

Karsten Østergaard Noe, Aarhus V, DK;

Jesper Mosegaard, Tilst, DK;

Brian Bunch Christensen, Aarhus N, DK;

Jens Rimestad, Skødstrup, DK;

Assignee:

LEGO A/S, Billund, DK;

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
A63F 13/65 (2014.01); G06V 10/75 (2022.01); G06V 20/64 (2022.01); A63F 13/213 (2014.01); A63H 33/08 (2006.01); G06K 9/62 (2022.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06N 5/04 (2023.01);
U.S. Cl.
CPC ...
A63F 13/65 (2014.09); A63F 13/213 (2014.09); A63H 33/08 (2013.01); G06K 9/627 (2013.01); G06K 9/6255 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06V 10/751 (2022.01); G06V 20/64 (2022.01);
Abstract

System and method for automatic computer aided optical recognition of toys, for example, construction toy elements, detection of those elements on digital images and associating the elements with existing information is presented. The method and system may recognize toy elements of various sizes invariant of toy element distance from the image acquiring device for example camera, invariant of rotation of the toy element, invariant of angle of the camera, invariant of background, invariant of illumination and without the need of predefined region where a toy element should be placed. The system and method may detect more than one toy element on the image and identify them. The system is configured to learn to recognize and detect any number of various toy elements by training a deep convolutional neural network.


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