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. 19, 2021

Filed:

Jun. 10, 2019
Applicant:

Capillary Technologies International Pte Ltd, Singapore, SG;

Inventors:

Sumandeep Banerjee, Karnataka, IN;

Subrat Panda, Karnataka, IN;

Doney Alex, Karnataka, IN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); G06K 9/34 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00362 (2013.01); G06K 9/00718 (2013.01); G06K 9/00744 (2013.01); G06K 9/00778 (2013.01); G06K 9/346 (2013.01); G06K 9/6256 (2013.01);
Abstract

A people detection system with feature space enhancement is provided. The system includes a memory having computer-readable instructions stored therein. The system includes a processor configured to access a plurality of video frames captured using one or more overhead video cameras installed in a space and to extract one or more raw images of the space from the plurality of video frames. The processor is further configured to process the one or more raw images to generate a plurality of positive image samples and a plurality of negative image samples. The positive image samples include images having one or more persons present within the space and the negative image samples comprise images without the persons. The processor is configured to apply at least one of a crop factor and a resize factor to the positive and the negative image samples to generate curated positive and negative image samples and to detect one or more persons present in the space using a detection model trained by the curated positive and negative image samples.


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