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:
Dec. 12, 2023

Filed:

Jan. 28, 2022
Applicant:

Ambarella International Lp, Santa Clara, CA (US);

Inventors:

Zhe Zhang, Shanghai, CN;

Zhikan Yang, Shanghai, CN;

Ruian Xu, San Jose, CA (US);

Assignee:

Ambarella International LP, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 13/207 (2018.01); H04N 9/07 (2006.01); H04N 5/225 (2006.01); H04N 13/254 (2018.01); H04N 13/257 (2018.01); H04N 5/33 (2023.01); H04N 23/12 (2023.01); H04N 23/56 (2023.01); H04N 23/73 (2023.01);
U.S. Cl.
CPC ...
H04N 13/207 (2018.05); H04N 5/33 (2013.01); H04N 13/254 (2018.05); H04N 13/257 (2018.05); H04N 23/12 (2023.01); H04N 23/56 (2023.01); H04N 23/73 (2023.01);
Abstract

An apparatus includes an interface circuit and a control circuit. The interface circuit may be configured to receive pixel data corresponding to a field of view of a camera. The control circuit may be configured to process the pixel data arranged as video frames and control an exposure time for capturing the pixel data and a turn on time of a structured light pattern to obtain a sequence of images comprising at least one image including the structured light pattern and at least one image where the structured light pattern is absent. The control circuit may be further configured to perform a depth analysis to generate depth information using the at least one image including the structured light pattern. The control circuit may store and execute an artificial neural network trained to (i) discern whether a face is at least one of a real face and a fake face, and (ii) make a liveness determination utilizing the depth information.


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