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基于尺度自适应局部时空特征的足球比赛视频中的多运动员行为表示 预览

Behavior representation of multi-athletes for football game video based on scale adaptive local spatial and temporal characteristics
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摘要 为提高足球比赛视频中的多运动员行为识别的准确率,提出一种基于尺度自适应局部时空特征的足球比赛视频中的多运动员行为表示方法,利用时空兴趣点来表示足球比赛视频中的多运动员行为。首先将足球比赛视频序列中的多运动员行为看作是三维空间中的时空兴趣点的集合,然后采用直方图量化技术将时空兴趣点集合量化为维数固定的直方图(即时空单词),最后采用K-means聚类算法生成时空码本。在聚类生成码本之前,对每个时空兴趣点都进行了归一化,以保证其缩放和平移不变性。实验结果表明,该方法能够大大减少足球比赛视频中的多运动员行为识别算法的计算量,显著提高识别的准确率。 In order to improve the accuracy of behavior recognition of multi-athletes in football game video, a behavior representation method of multi-athletes for video football game based on scale adaptive local spatial and temporal characteristics was put forward. Behavior recognition was carried on using spatial-timporal interest point to represent behavior of multi-athletes in video football game. Firstly, multi-athletes behavior in the sequence of video football game was regarded as a collection of spatial-timporal interest points in three-dimensional space. Secondly, the set of spatial-temporal interest points was quantified as histogram which has fixed dimension ( ie temporal word) by using quantitative technique of histogram. Finally, spatial- temporal codebook was generated by using K-means clustering algorithm. Each spatial-timporal interest point was normalized to ensure its scaling and translation invariance before clustering codebook generated. Experimental results show that the proposed method can greatly reduce the computational amount of the algorithm, and the accuracy of recognition can be significantly improved.
作者 王智文 蒋联源 王宇航 王日凤 张灿龙 黄镇谨 王鹏涛 WANG Zhiwen, JIANG Lianyuan , WANG Yuhang, WANG Rifeng, ZHANG Canlong, HUANG Zhenjin, WANG Pengtao( 1. College of Computer Science and Communication Engineering, Guangxi University of Science and Technology, Liuzhou Guangxi 545006, China 2. Guangxi Experiment Center of Information Science, Guilin University of Electronic Technology, Guilin Guangxi 541004, China; 3. Institute of Automobile and Traffic Engineering, Guilin University of Aerospace Technology, Guilin Guangxi 541004, China; 4. College of Computer Science & Information Technology, Guangxi Normal University, Guilin Guangxi 541004, China ; 5. College of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou Guangxi 545006, China)
出处 《计算机应用》 CSCD 北大核心 2016年第8期2134-2138,共5页 journal of Computer Applications
基金 国家自然科学基金资助项目(61462008,61440017,61365009) 广西自然科学基金项目(2013GxNsFAA019336,2014GXNSFAA118368) 广西信息科学实验中心开放基金项目(KF1403) 广西科技大学博士基金项目(院科博12214) 2015年广西科技大学创新团队项目.
关键词 时空兴趣点 多运动员行为表示 行为识别 K-MEANS聚类算法 时空特征检测操作数 spatial-temporal interest point multi-athletes behavior representation behavior recognition K-means clustering algorithm spatial-temporal feature detection operand
作者简介 通信作者电子邮箱wzw69@126.com王智文(1969-),男,湖南邵东人,教授,博士,主要研究方向:机器学习、计算机视觉、移动目标检测、行为识别; 蒋联源(1981-)男,广西全州人,副教授,硕士,主要研究方向:图形图像处理; 王宇航(1994-),男,湖南邵东人,主要研究方向:图像处理; 王日凤(1974-),女广西桂林人,副教授,博士,主要研究方向:医学图像处理; 张灿龙(1975-),男,湖南娄底人,副教授,博士,主要研究方向:图像处理; 黄镇谨(1975-)男,广西柳州人,副教授,硕士,主要研究方向:数据挖掘; 王鹏涛(1990-),男,陕西西安人,硕士研究生,主要研究方向:图像处理。
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