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基于异常检测和转移学习的运动视频自动标注框架

A framework for automatic sports video annotation with anomaly detection and transfer learning
课程网址: http://videolectures.net/machine_de_campos_video_annotation/  
主讲教师: Teofilo De Campos
开课单位: 萨里大学
开课时间: 2013-08-06
课程语种: 英语
中文简介:
本文描述了一个可以自动注释视频的系统,并说明了它在网球游戏中的应用。提出了一种统一的装置,采用贝叶斯推理框架。这得到认知记忆体系结构的支持,该体系结构允许系统以最低认知水平存储原始视频数据并且其语义注释具有增加的抽象水平,直到确定游戏的分数。系统中还嵌入了一组机制,用于检测由输入数据中的域更改引起的异常。一旦检测到异常,就会触发转移学习方法,使知识适应新的领域,例如新的运动方式。我们还提出了规则归纳的通用框架,这在自适应注释系统的背景下至关重要。
课程简介: This paper describes a system that can automatically annotate videos and illustrates its application to tennis games. A unified apparatus is proposed, cast in a Bayesian reasoning framework. This is supported by a cognitive memory architecture that allows the system to store raw video data at the lowest cognitive level and its semantic annotation with increasing levels of abstraction up to determining the score of a game. Also embedded in the system is a set of mechanisms to detect anomalies caused by a change of domain in the input data. Once an anomaly is detected, transfer learning methods are triggered to adapt the knowledge to new domains, such as new sport modalities. We also present a generic framework for rule induction that is crucial in the context of an adaptive annotation system.
关 键 词: 注释视频; 网球游戏; 贝叶斯推理
课程来源: 视频讲座网
最后编审: 2019-05-15:cwx
阅读次数: 59