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.
Patent No.:
Date of Patent:
Aug. 01, 2023
Filed:
Jun. 26, 2020
Apparatus and methods for determining multi-subject performance metrics in a three-dimensional space
Intel Corporation, Santa Clara, CA (US);
Nelson Leung, San Jose, CA (US);
Jonathan K. Lee, San Carlos, CA (US);
Bridget L. Williams, San Francisco, CA (US);
Sameer Sheorey, Sunnyvale, CA (US);
Amery Cong, San Francisco, CA (US);
Mehrnaz Khodam Hazrati, San Jose, CA (US);
Sabar Mourad Souag, Beaverton, OR (US);
Adam Marek, Gdansk, PL;
Pawel Pieniazek, Gdansk, PL;
Bogna Bylicka, Gdansk, PL;
Jakub Powierza, Gdansk, PL;
Anna Banaszczyk-fiszer, Gdansk, PL;
Intel Corporation, Santa Clara, CA (US);
Abstract
Apparatus and methods for extraction and calculation of multi-person performance metrics in a three-dimensional space. An example apparatus includes a detector to identify a first subject in a first image captured by a first image capture device based on a first set of two-dimensional kinematic keypoints in the first image, the two-dimensional kinematic keypoints corresponding to a joint of the first subject, the first image capture device associated with a first view of the first subject, a multi-view associator to verify the first subject using the first image and a second image captured by a second image capture device, the second image capture device associated with a second view of the first subject, the second view different than the first view, and a keypoint generator to generate three-dimensional keypoints for the first subject using the first set of two-dimensional kinematic keypoints.