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广播体育视频中的战术分析研究
其他题名Tactics Analysis in Broadcast Sports Video
张奕
学位类型工学博士
导师卢汉清
2010-05-20
学位授予单位中国科学院研究生院
学位授予地点中国科学院自动化研究所
学位专业模式识别与智能系统
关键词体育视频分析 语义理解 球和球员轨迹提取 战术分析 Sports Video Analysis Semantics Ball And Player Trajectory Extraction Tactic Analysis
摘要广播体育视频分析是近年来视频内容分析领域的一项重要研究内容,因其存在巨大的潜在应用背景而受到了广泛的关注。广播体育视频具有数据容易获取的优点,研究的实用性强,但是由于广播体育视频质量较低,干扰多,分析难度较大。传统体育视频分析主要为观众服务,根据观众的兴趣,解析视频中的各类语义信息,对视频进行自动编辑处理,满足观众的不同需求。本文则主要从运动员、教练员以及体育科研人员的需求出发,在广播体育视频提取其关注的战术信息,并将视频中的战术分门别类地呈现给用户,为其训练提供有力的帮助。本文除了从基本视觉特征出发,进行特定战术事件的推理之外,主要采用了基于球和球员轨迹的方法来进行战术的提取。首先针对广播体育视频中球和球员检测跟踪存在的挑战,提出了具有高容错性的球和球员轨迹提取框架,解决了检测跟踪中的错误传播问题。球类比赛中的各类战术都是通过球和球员的运动实现的,球和球员轨迹作为重要的中层特征表示,包含了球和球员的运动信息,因而对战术类型具有很强的表达能力,是理想的特征表示。基于轨迹上的运动特征,本文提出了具有普适性的广播体育视频战术分析的基本框架结构,解决不同体育项目中各类战术的挖掘和分类问题。本文的主要贡献包括: 1)运用比赛视频中的语义信息直接进行战术相关的推理,通过战术的特征序列模型匹配,发现视频中与特定战术模型匹配的片段,以此作为检测该战术的手段。 2)针对广播体育视频的特点对球和球员轨迹提取提出的挑战,设计了分解整合的球和球员轨迹提取框架,提高球和球员轨迹提取的容错性,防止错误的累积和传播,以适应广播体育视频中的复杂环境。 3)以球和球员轨迹作为中层特征表示,从提取到的球和球员轨迹上的获得球和球员的运动特征序列,用于战术的检测分类。提出衡量轨迹间局部相似性的轨迹相似距离,作为基于轨迹的战术检测分类的基本相似度度量,并以此为基础,运用半监督和监督的方法进行战术检测和分类。 4)提出用后缀树描述轨迹局部特征的模型,并利用该模型进行关键子序列模式的选择,去除轨迹中与关心的战术无关以及冗余的子序列模式,在提高训练和分类效率的同时也改善了战术分类的准确性。
其他摘要Sports video content has been proliferating with the development of the multimedia and communication technology. As a result, sports video analysis has attracted significant attention from both academia and industry. Most existing work on sports video analysis mainly focuses on semantic analysis which aims to detect semantic events in the game. Different from semantic analysis which is totally audience oriented, tactic analysis serving for professionals has been paid more attention to recently. Professionals such as coaches and players are more interested in the tactics frequently used in the games rather than “objective” events. Presenting professionals with tactics in the game can assist them to establish strategy and improve training effect. Besides the introduction of direct inference from low level features to tactics, the thesis mainly focuses on the ball and player trajectory based tactic analysis. In ball games, tactics can be deduced from the movement of the ball and players. Therefore, temporal and spatial trajectories of the ball and players become the appropriate feature for tactic analysis. A robust decomposition-integration framework for ball and player trajectory extraction is proposed, which is specially designed to tackle the challenges in broadcast sports video. Trajectory similarity is defined and tactics are discovered with the classification of ball and player trajectories. The contribution of the thesis consists of: 1)An inference scheme is proposed to discover tactics with low-level features and semantics. The inference is based on the model of the view direction sequence and the rule of the game. 2)A robust decomposition-integration framework with collaborative ball and player trajectory extraction is proposed. The novel framework uses decomposition to contain error in local area and uses a fault-tolerant integration scheme to achieve global optimal trajectory. 3)Motion information is extracted from the trajectories by taking ball and player trajectories as mid-level features. Local feature based trajectory similarity is defined and semi-supervised and supervised tactic detection and classification is conducted with the trajectory similarity measurement. 4)Suffix tree is introduced to describe the local feature of trajectories. Key sub-trajectories are selected with the suffix tree model and most irrespective samples are discarded to improve the effectiveness and efficiency of the training process.
馆藏号XWLW1436
其他标识符200618014628042
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6237
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
张奕. 广播体育视频中的战术分析研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2010.
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