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. 23, 2019

Filed:

Jul. 21, 2017
Applicant:

Altumview Systems Inc., Burnaby, CA;

Inventors:

Xing Wang, Burnaby, CA;

Mehdi Seyfi, North Vancouver, CA;

Minghua Chen, Coquitlam, CA;

Him Wai Ng, Coquitlam, CA;

Jie Liang, Coquitlam, CA;

Assignee:

Altum View Systems Inc., Port Moody, BC, CA;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06N 3/04 (2006.01); G06T 7/11 (2017.01); G06T 7/246 (2017.01); G06K 9/20 (2006.01); G06K 9/62 (2006.01); G06N 3/06 (2006.01); G06N 3/08 (2006.01); G06T 5/50 (2006.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G06N 3/04 (2013.01); G06K 9/00228 (2013.01); G06K 9/00268 (2013.01); G06K 9/00275 (2013.01); G06K 9/00288 (2013.01); G06K 9/2054 (2013.01); G06K 9/4628 (2013.01); G06K 9/6232 (2013.01); G06K 9/6256 (2013.01); G06K 9/6274 (2013.01); G06N 3/0454 (2013.01); G06N 3/06 (2013.01); G06N 3/08 (2013.01); G06T 5/50 (2013.01); G06T 7/11 (2017.01); G06T 7/248 (2017.01); G06K 9/00402 (2013.01); G06K 9/6289 (2013.01); G06K 2009/00322 (2013.01); G06K 2209/15 (2013.01); G06T 2200/28 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/20224 (2013.01); G06T 2207/30201 (2013.01); G06T 2210/12 (2013.01);
Abstract

Embodiments described herein provide various examples of a face detection system, based on using a small-scale hardware convolutional neural network (CNN) module configured into a multi-task cascaded CNN. In some embodiments, a subimage-based CNN system can be configured to be equivalent to a large-scale CNN that processes the entire input image without partitioning such that the output of the subimage-based CNN system can be exactly identical to the output of the large-scale CNN. Based on this observation, some embodiments of this patent disclosure make use of the subimage-based CNN system and technique on one or more stages of a cascaded CNN or a multitask cascaded CNN (MTCNN) so that a larger input image to a given stage of the cascaded CNN or the MTCNN can be partitioned into a set of subimages of a smaller size. As a result, each stage of the cascaded CNN or the MTCNN can use the same small-scale hardware CNN module that is associated with a maximum input image size constraint.


Find Patent Forward Citations

Loading…