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US12586237B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12586237-B2 |
| Application number | US-202318216635-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 30, 2023 |
| Priority date | Jul 15, 2022 |
| Publication date | Mar 24, 2026 |
| Grant date | Mar 24, 2026 |
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A device for detecting a goaltending event includes circuitry configured to: determine a real-life position of a basketball from a video stream; detect an impact on the basketball from the movement of the basketball captured in the video stream; output a signal indicating a detected goaltending event based on the detected impact and the real-life position of the basketball.
Opening claim text (preview).
What is claimed is: 1 . A device-system for detecting a goaltending event, comprising: a plurality of cameras; and circuitry configured to: receive a video stream from the cameras; determine a real-life position of a basketball from a video stream by determining the pixels in the video stream that correspond to the basketball; detect an impact on the basketball from the movement of the basketball captured in the video stream; determine a real-life skeletal feature position; and output a signal indicating a detected goaltending event based on the detected impact and the real-life position of the basketball; wherein the signal indicating the detected goaltending event is further based on the real-life position of the basketball relative to a real-life position of a basketball rim and the real-life skeletal feature position. 2 . The system according to claim 1 , wherein the signal includes a time segment indicative of the position of the detected goaltending event within the video stream. 3 . The system according to claim 1 , wherein the impact is detected based upon the deviation of movement of the basketball from a polynomial path. 4 . The system according to claim 1 , wherein the real-life position of the basketball is determined by the steps of: performing object detection on a frame from the video stream to identify the position of one or more candidate basketballs within the frame using a machine learning technique. 5 . The system according to claim 1 , further comprising a content providing device wherein the content providing device is configured to generate a clip of video based upon the signal output from the device. 6 . The system of claim 1 , wherein the circuitry is configured to determine the real-life position of the basketball from the video stream by determining whether each pixel in the video stream is the center of the basketball. 7 . The system according to claim 1 , wherein the real-life position of the basketball rim is determined by the steps of: converting one or more segments of a frame in the video stream into a colour space reference image, the reference colour being the colour of the basketball rim; performing edge detection on the colour space reference image; and determining the real-life position of the basketball rim based upon the edge detected colour space reference image. 8 . The system according to claim 7 , wherein the one or more segments include a segment bounding the basketball rim. 9 . The system of claim 1 , wherein the circuitry is configured to determine the real-life position of the basketball from the video stream by placing reference circles having different radii over each pixel and determining whether there is an edge of a circle at a number of points distributed along the circumference of the reference circles. 10 . The system of claim 9 , wherein the circuitry is configured to determine the real-life position of the basketball from the video stream by further applying a score to each pixel to indicate a likelihood of each pixel being the center of the basketball. 11 . A method for detecting a goaltending event, comprising: receiving a video stream from cameras; determining a real-life position of a basketball from a video stream by determining the pixels in the video stream that correspond to the basketball; detecting an impact on the basketball from the movement of the basketball captured in the video stream; determining a real-life skeletal feature position; and outputting a signal indicating a detected goaltending event based on the detected impact and the real-life position of the basketball, wherein the signal indicating the detected goaltending event is further based on the real-life position of the basketball relative to a real-life position of a basketball rim and the real-life skeletal feature position. 12 . The method according to claim 11 , wherein the signal includes a time segment indicative of the position of the detected goaltending event within the video stream. 13 . The method according to claim 11 wherein the impact is detected based upon the deviation of movement of the basketball from a polynomial path. 14 . The method according to claim 11 , wherein the real-life position of the basketball is determined by the steps of: performing object detection on a frame from the video stream to identify the position of one or more candidate basketballs within the frame using a machine learning technique. 15 . A method comprising generating a clip of video based upon the output signal and a method according to claim 11 . 16 . A non-transitory computer readable medium storing a program product comprising computer readable instructions which, when loaded onto a computer, configures the computer to perform the method according to claim 11 . 17 . The method of claim 11 , wherein determining the real-life position of the basketball from the video stream includes placing reference circles having different radii over each pixel and determining whether there is an edge of a circle at a number of points distributed along the circumference of the reference circles. 18 . The system of claim 11 , wherein determining the real-life position of the basketball from the video stream includes determining whether each pixel in the video stream is the center of the basketball. 19 . The method according to claim 11 , wherein the real-life position of the basketball rim is determined by the steps of: converting one or more segments of a frame in the video stream into a colour space reference image, the reference colour being the colour of the basketball rim; performing edge detection on the colour space reference image; and determining the real-life position of the basketball rim based upon the edge detected colour space reference image. 20 . The method according to claim 19 , wherein the one or more segments include a segment bounding the basketball rim.
Ball; Puck · CPC title
Training; Learning · CPC title
Video; Image sequence · CPC title
Analysis of motion (motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51) · CPC title
Basketball · CPC title
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