首页> 外文会议>International Conference on Multimedia Content Analysis and Mining(MCAM 2007); 20070630-0701; Weihai(CN) >Players and Ball Detection in Soccer Videos Based on Color Segmentation and Shape Analysis
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Players and Ball Detection in Soccer Videos Based on Color Segmentation and Shape Analysis

机译:基于颜色分割和形状分析的足球视频中球员和球的检测

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摘要

This paper proposes a scheme to detect and locate the players and the ball on the grass playfield in soccer videos. We put forward a shape analysis-based approach to identify the players and the ball from the roughly extracted foreground, which is obtained by a trained, color histogram-based playfield detector and connected component analysis. We employ Euclidean distance transform to extract skeletons for every foreground blob, and then perform shape analysis to remove false alarms (non-player and non-ball blobs) and cutoff the artifacts (mostly due to playfield lines) based on skeleton pruning and reverse Euclidean distance transform. Results are given to demonstrate the proposed algorithm works well in soccer video clips.
机译:本文提出了一种在足球视频中的草地运动场上检测并定位球员和球的方案。我们提出了一种基于形状分析的方法,从经过粗略提取的前景中识别球员和球,这是由经过训练的基于颜色直方图的运动场检测器和相连的组件分析所获得的。我们采用欧氏距离变换为每个前景Blob提取骨骼,然后执行形状分析以基于骨骼修剪和反向Euclidean消除错误警报(非玩家和非球状Blob)并切断伪像(主要是由于运动场线条)距离变换。结果表明该算法在足球视频剪辑中效果良好。

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