Method for detecting goal events in soccer video based on hidden markov model

A technology for event detection and scoring, applied in the field of sports video semantic analysis, can solve the problems of time-consuming, limited detection performance, and inability to more effectively mine the potential rules of semantic events, etc., to achieve simple construction process, alleviate semantic gap, and improve detection performance effect

Inactive Publication Date: 2012-03-28
XIDIAN UNIV
View PDF3 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the process of building a model with this method is time-consuming, and hidden state variables are not used, so th

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 for detecting goal events in soccer video based on hidden markov model
  • Method for detecting goal events in soccer video based on hidden markov model
  • Method for detecting goal events in soccer video based on hidden markov model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] 1. Introduction to basic theory

[0026] Football games are very popular among the public, but the data volume of a game video is huge, and the exciting events that the audience is interested in are usually only a small part of the whole game. The semantic detection of is crucial in the field of football video semantic analysis. However, football game videos have a specific structure. Deeply and accurately digging out this internal structural feature and connection to establish an effective football game video structure model makes semantic detection of exciting events possible, which is of great importance in the field of semantic analysis of sports videos. theoretical value and market application prospects.

[0027] Football game video clips can be divided into goal video clips and non-goal video clips. Each clip includes long shots, medium shots, close-up shots, audience shots and playback shots. Through the analysis of a large number of real game videos, it is foun...

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 discloses a method for detecting goal events in a soccer video based on a hidden markov model. By the method, the problems of complicated event detection system model and low detection rate in the prior art are solved. The method comprises the following steps of: firstly, performing physical shot segmenting and semantic shot labeling on a training video and a test video, and respectively forming a training data set and a test data set respectively by using acquired semantic shot sequences; secondly, calculating an initial parameter of the hidden markov model according to the training data set; thirdly, training an initial model by adopting a Baum-Welch algorithm and the training data set and establishing the hidden markov model for the goal events; fourthly, calculating a probability of the model for generating training data by adopting a forward algorithm and acquiring a judgment threshold value; and finally, calculating a probability of the model for generating test data and detecting the goal event in the test video according to the judgment threshold value. By the method, detection for semantic goal events can be realized accurately; and the method is applied to the field of semantic analysis, such as detection for wonderful events in the soccer video and the like.

Description

technical field [0001] The invention belongs to the field of video information retrieval, relates to sports video semantic analysis, and can be used in football video goal event detection to detect goal events quickly and accurately. Background technique [0002] Sports video has attracted extensive attention from researchers and all walks of life because of its huge audience and huge commercial value. Automatic detection of exciting events in sports videos has always been a hot spot in the field of video semantic analysis. The difficulty lies in the need to solve the semantic gap between low-level features and high-level semantics. Scholars at home and abroad have conducted extensive research on this and achieved a lot of research. results. [0003] The current methods based on machine learning mainly include: [0004] (1) Ding Y, Fan G L. Sports Video Mining via Multichannel Segmental Hidden Markov Models [J] IEEE Trans. on Multimedia, 2009, 11(7): 1301-1309. Based on t...

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
IPC IPC(8): G06K9/62G06F17/30
Inventor 同鸣谢文娟张伟
Owner XIDIAN UNIV
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
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap