Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Method and system for judging goals for basketball game video

A basketball and video technology, applied in the field of video goal determination in basketball games, can solve the problems of inability to handle real-time video streams and difficult training, and achieve the effect of reducing misjudgments and improving accuracy.

Active Publication Date: 2019-10-01
新华智云科技有限公司
View PDF7 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method uses a recursive convolutional neural network, and this type of network is often difficult to train due to the problem of gradient disappearance; at the same time, this method can only process a single video clip to determine whether the video clip is a goal clip, but cannot process real-time video flow

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and system for judging goals for basketball game video
  • Method and system for judging goals for basketball game video
  • Method and system for judging goals for basketball game video

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0065] Embodiment 1, a kind of method that is used for basketball match video goal judgment, as Figures 1 to 3 shown, including the following steps:

[0066] S1. Obtain all shooting moments in the video to be determined, and obtain corresponding shooting clips according to the shooting moments.

[0067] First, the detection model is obtained based on deep learning algorithm training, and each video frame in the video to be determined is detected by using the detection model, and the position, size and category (basketball / basket) of the basketball and the basket in each video frame are output, that is, the video frame The detection frame information of basketball and basket. According to the position, size and category (basketball / basketball) information of the basketball and basket in each video frame, it is judged whether there is a shot. If there is, the moment corresponding to the video frame is the moment of shooting. video clips to get shot clips.

[0068] The specif...

Embodiment 2

[0113] Embodiment 2, change goal data in the embodiment 1 step S2 from "goal, no goal" to "0 (i.e. no goal), 1 point (free throw), 2 points, 3 points", Be about to change the scoring model of the two classifications of embodiment 1 judgment goal / no goal into the scoring model of the four classifications of judging no goal, 1 point (free throw), 2 points, and 3 points, and all the other are equal to the implementation example 1.

[0114] The details of constructing the scoring model are as follows:

[0115] Manually mark all the sample shooting clips, and the tag content is the goal data of the video clip. The goal data includes 0 (no goal), 1 point (free throw), 2 points, 3 points, and the sample shooting clips and their Goal data. And the sample shot segment and its goal data are randomly divided into a detection video training set, a video verification set and a video test set according to Example 1.

[0116] The two-stream network TSN (Temporal Segment Networks, time dom...

Embodiment 3

[0121] Embodiment 3, a kind of system that is used for basketball game video goal determination, such as Figure 4 Shown include:

[0122] The game image acquisition module 1 is used to acquire the game image and its label information, and divide the game image and its label information into an image training set, an image verification set and an image test set according to a preset ratio. The label information includes basketball and basket the position, size and type of;

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a method for judging goals for a basketball game video. The method comprises the following steps: obtaining game images and annotation information thereof, and dividing the game images and the annotation information thereof into an image training set, an image verification set and an image test set according to a preset proportion; utilizing the image training set to trainthe detection model to obtain a plurality of detection intermediate models, utilizing the image verification set and the image test set to carry out verification test on each detection intermediate model, and obtaining an optimal detection intermediate model as a detection model output; obtaining a video frame of the to-be-judged video, inputting the video frame into the detection model, and obtaining positions, sizes and categories of a basketball and a basket corresponding to the video frame; and according to the positions, sizes and categories of the basketballs and the basketballs, judging the shooting time, and generating corresponding shooting segments according to the shooting time. The method for judging goals for a basketball game video can automatically detect shooting time in the to-be-judged video and generate the corresponding shooting segment, so that a user can conveniently select the shooting segment according to actual needs.

Description

technical field [0001] The invention relates to the field of video detection, in particular to a method and system for judging a goal in a basketball game video. Background technique [0002] The current method of judging the goal in the basketball game video is as follows: [0003] Manual judgment: People watch the basketball game video throughout the whole process, and manually judge whether a goal is scored during the viewing process. Using this method to judge has the highest accuracy, but the work efficiency is too low and the time cost is too high, especially for all levels of basketball. There are dozens to hundreds of games every day, and it is impossible to manually screen all the goals in the videos. [0004] "Basketball Goal Judgment Method and System Based on Image Processing" (CN107303428A) proposes to detect the spatial position of the basketball in each image frame, and determine the trajectory of the basketball according to the connection line of the spatial...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V20/42
Inventor 陈雷雷王灿进
Owner 新华智云科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products