• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Image Processing, IEEE Transactions on >Multiple Player Tracking in Sports Video: A Dual-Mode Two-Way Bayesian Inference Approach With Progressive Observation Modeling
【24h】

Multiple Player Tracking in Sports Video: A Dual-Mode Two-Way Bayesian Inference Approach With Progressive Observation Modeling

机译：运动视频中的多人跟踪：具有渐进式观察模型的双模式双向贝叶斯推理方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Multiple object tracking (MOT) is a very challenging task yet of fundamental importance for many practical applications. In this paper, we focus on the problem of tracking multiple players in sports video which is even more difficult due to the abrupt movements of players and their complex interactions. To handle the difficulties in this problem, we present a new MOT algorithm which contributes both in the observation modeling level and in the tracking strategy level. For the observation modeling, we develop a progressive observation modeling process that is able to provide strong tracking observations and greatly facilitate the tracking task. For the tracking strategy, we propose a dual-mode two-way Bayesian inference approach which dynamically switches between an offline general model and an online dedicated model to deal with single isolated object tracking and multiple occluded object tracking integrally by forward filtering and backward smoothing. Extensive experiments on different kinds of sports videos, including football, basketball, as well as hockey, demonstrate the effectiveness and efficiency of the proposed method.
机译：多对象跟踪（MOT）是一项非常具有挑战性的任务，但对许多实际应用而言却具有根本的重要性。在本文中，我们关注于跟踪体育视频中的多个运动员的问题，由于运动员的突然动作及其复杂的交互作用，这更加困难。为了解决此问题中的困难，我们提出了一种新的MOT算法，该算法在观测建模级别和跟踪策略级别都做出了贡献。对于观察建模，我们开发了一种渐进式观察建模过程，该过程能够提供强大的跟踪观察结果，并极大地方便了跟踪任务。对于跟踪策略，我们提出了一种双模式双向贝叶斯推理方法，该方法可以在脱机通用模型和在线专用模型之间动态切换，以通过前向滤波和后向平滑处理对单个孤立对象跟踪和多个遮挡对象跟踪进行整体处理。在包括足球，篮球和曲棍球在内的各种体育视频上的大量实验证明了该方法的有效性和效率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号