Lattice-Based Anomaly Rectification for Sport Video Annotation
Lattice-Based Anomaly Rectification for Sport Video Annotation
复制标题
基于格的运动视频注释异常校正
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
W. Christmas
中科院分区：
文献类型：
--
作者：
Aftab Khan;David Windridge;T. D. Campos;J. Kittler;W. Christmas
异常检测在文献中作为以无监督的方式确定学习域是否以根本的方式改变的手段而受到广泛关注。这可能需要放弃持续的自适应学习，并在新的领域中启动新的学习过程。一个相关的问题是异常纠正;现有的学习机制的适应域的变化。作为这一概念的一个具体实例，本文研究了一种新的基于格的HMM归纳策略，用于任意法庭游戏环境。我们测试（在真实的和模拟域）的方法，以适应规则结构的变化，从网球单打网球双打的能力。我们的长期目标是建立一个通用的系统转移游戏规则的推理。
Anomaly detection has received much attention within the literature as a means of determining, in an unsupervised manner, whether a learning domain has changed in a fundamental way. This may require continuous adaptive learning to be abandoned and a new learning process initiated in the new domain. A related problem is that of anomaly rectification; the adaptation of the existing learning mechanism to the change of domain. As a concrete instantiation of this notion, the current paper investigates a novel lattice-based HMM induction strategy for arbitrary court-game environments. We test (in real and simulated domains) the ability of the method to adapt to a change of rule structures going from tennis singles to tennis doubles. Our long term aim is to build a generic system for transferring game-rule inferences.