Football item detecting system with four-layer structure in sports video and realization method thereof

Abstract

The invention provides a football item detecting system with a four-layer structure in a sports video and a realization method thereof. The realization method comprises the following steps of: analyzing the whole video by shot boundary detection, classifying adjacent clips with the same switching mode and the same movement characteristic into one class, naming the adjacent clips as a video folder, counting the duration time of video clips at the same time, mapping the duration time to a codebook to make a histogram, and comparing the histogram with the conventional template to realize first-layer classification; at the second stage, extracting key frames of the clips, extracting local characteristics and overall characteristics, performing characteristic mapping in a multi-codebook mode, and classifying master scenes by using a support vector machine (SVM) to obtain a corresponding key frame-based picture score; at the third stage, mapping clips represented by the key frames to a corresponding video folder and weighting to obtain a corresponding classification result; and finally performing post-fusion on a first-time classification result to obtain a final result. The system has higher identification accuracy and speed, can effectively identify sports types and is suitable for machine marking and advertisement recommendation and the like of sports programs.

Description

technical field [0001] The invention belongs to the field of multimedia information processing and retrieval and relates to a sports video classification method, and relates to the statistical analysis of the composition characteristics of sports video shots and the extraction and classification of video bottom layer features. The present invention introduces the analysis and statistics of different types of sports lens editing methods and scene composition to form an editing template, and on the basis of the system's SVM classification of the key frames of the lens, it is effectively combined, and the time period for scoring the key frames is used. It is merged with the template matching result of the editing method. A four-layer system detection system for high-precision identification of football events in sports videos is proposed. After replacing the corresponding training samples, it can effectively identify other sports types. It is suitable for machine labeling of spor...

AI Technical Summary

Problems solved by technology

[0005] In the practical process, we found that due to the redundancy of shots and the robustness of feature classification algorithms at this stage, the results are not ideal

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