US 12,450,902 B2
Systems, methods, and computer-program products for assessing athletic ability and generating performance data
Corey Leon Yates, Roswell, GA (US); and Alfonzo Thurman, II, Snellville, GA (US)
Assigned to Recruiting Analytics LLC, Atlanta, GA (US)
Filed by Recruiting Analytics LLC, Atlanta, GA (US)
Filed on Jun. 7, 2023, as Appl. No. 18/331,100.
Application 18/331,100 is a continuation of application No. 17/002,331, filed on Aug. 25, 2020, granted, now 11,710,317.
Claims priority of provisional application 63/011,976, filed on Apr. 17, 2020.
Claims priority of provisional application 62/987,809, filed on Mar. 10, 2020.
Claims priority of provisional application 62/985,316, filed on Mar. 4, 2020.
Prior Publication US 2023/0316750 A1, Oct. 5, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06V 20/40 (2022.01); A61B 5/11 (2006.01); A61B 5/117 (2016.01); A63B 24/00 (2006.01); G06T 7/246 (2017.01); G06V 40/20 (2022.01)
CPC G06V 20/42 (2022.01) [A61B 5/1118 (2013.01); A61B 5/1128 (2013.01); A61B 5/117 (2013.01); A63B 24/0003 (2013.01); A63B 24/0021 (2013.01); A63B 24/0062 (2013.01); G06T 7/248 (2017.01); G06V 40/25 (2022.01); A61B 2503/10 (2013.01); G06T 2207/30221 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for generating athlete performance data using computer-vision analysis and identifying athletes with desired characteristics, the method comprising:
accessing a video, the video comprising a plurality of frames depicting an athlete, each of the plurality of frames having an associated time-stamp;
identifying, using a computer-vision system, a location designator associated with the athlete in each frame of the plurality of frames;
identifying, using the computer-vision system, a location designator associated with a reference element in each frame of the plurality of frames;
identifying, using the computer-vision system, a coordinate distance between the location designator associated with the athlete and the location designator associated with the reference element in each frame of the plurality of frames;
converting, using the computer-vision system, each coordinate distance to a corresponding physical distance;
generating performance data for the athlete using the converted physical distance at each time-stamp;
updating an athlete profile associated with the athlete to include the generated performance data;
receiving at least one user-selected parameter associated with at least one desired characteristic;
selecting the athlete profile from a plurality of athlete profiles based on the at least one user-selected parameter; and
identifying the athlete profile as a best-fit match with the at least one user-selected parameter.