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:
Aug. 27, 2024

Filed:

Aug. 17, 2020
Applicant:

Mitsubishi Electric Research Laboratories, Inc., Cambridge, MA (US);

Inventors:

Zafer Sahinoglu, Costa Mesa, CA (US);

Kuan-Chuan Peng, Charlestown, MA (US);

Alan Sullivan, Middleton, MA (US);

William Yerazunis, Acton, MA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
B66B 1/46 (2006.01); B66B 1/28 (2006.01); B66B 1/34 (2006.01); B66B 3/00 (2006.01); G06F 3/14 (2006.01); G06F 18/214 (2023.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06V 10/44 (2022.01); G06V 20/62 (2022.01); H04N 23/54 (2023.01); G06V 30/10 (2022.01);
U.S. Cl.
CPC ...
B66B 1/468 (2013.01); B66B 1/28 (2013.01); B66B 1/3461 (2013.01); B66B 3/002 (2013.01); G06F 3/14 (2013.01); G06F 18/214 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06V 10/44 (2022.01); G06V 20/62 (2022.01); H04N 23/54 (2023.01); B66B 2201/101 (2013.01); B66B 2201/103 (2013.01); B66B 2201/4615 (2013.01); B66B 2201/4623 (2013.01); B66B 2201/4638 (2013.01); B66B 2201/4653 (2013.01); G06V 30/10 (2022.01);
Abstract

Systems, methods and devices for real-time contactless elevator service operation of an elevator includes a trained neural network (TNN) model. The TNN model is trained using a training processor with augmented datasets as a synthetic training dataset, to later perform elevator identifier recognition. The augmented data sets are generated from synthetic text images, the synthetic text images are augmented with different geometrical parameters and visual parameters to a predetermined number of variations in appearance to a set of training elevator identifiers. A camera captures a user image. A text image portion from the user image is extracted using the TNN model, and detects an elevator identifier in the extracted text image portion using the extracted text image portion and the TNN model. The detected elevator identifier is displayed for user confirmation or user cancellation, and upon user confirmation, generates a control command based the detected elevator identifier associated with an elevator service.


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