首页> 外文期刊>Journal of visual communication & image representation >A novel hierarchical data association with dynamic viewpoint model for multiple targets tracking
【24h】

A novel hierarchical data association with dynamic viewpoint model for multiple targets tracking

机译:具有动态视点模型的新型分层数据关联用于多目标跟踪

获取原文
获取原文并翻译 | 示例
           

摘要

A new framework of hierarchical data association tracking (HDAT) with branch partition, candidate upgrading and incremental motion pairing inference is proposed to resolve the problem of online multiple targets tracking. Branch partition divides the process into several independent parts so as to reduce the computational complexity on affinity. Candidate upgrading improves the robustness of target initialization by tracking potential targets and incremental motion pairing inference could benefit the occlusion handling. Furthermore, a dynamic viewpoint model (DVM) and its iterative computation algorithm are developed for tracking multiple targets under moving camera videos. Extensive data experiments on several public benchmarks show that the presented approach achieves comparable results to state-of-the-art on static camera videos and promising results on moving camera videos, and moreover, the runtime performance is significantly improved. (C) 2015 Elsevier Inc. All rights reserved.
机译:为了解决在线多目标跟踪问题,提出了一种新的具有分支划分,候选升级和增量运动配对推理的分层数据关联跟踪框架。分支分区将过程分为几个独立的部分,以减少相关性的计算复杂性。候选升级通过跟踪潜在目标来提高目标初始化的鲁棒性,增量运动配对推断可能会有利于遮挡处理。此外,开发了动态视点模型(DVM)及其迭代计算算法来跟踪运动摄像机视频下的多个目标。在多个公共基准上进行的大量数据实验表明,所提出的方法在静态摄像机视频上可获得与最新技术相当的结果,而在运动摄像机视频上可获得可观的结果,此外,运行时性能得到了显着提高。 (C)2015 Elsevier Inc.保留所有权利。

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