首页> 外文会议>Annual CHI conference on human factors in computing systems >Facilitating Multiple Target Tracking using Semantic Depth of Field (SDOF)
【24h】

Facilitating Multiple Target Tracking using Semantic Depth of Field (SDOF)

机译:使用语义景深(SDOF)促进多个目标跟踪

获取原文

摘要

Users of radar control systems and monitoring applications have to constantly extract essential information from dynamic scenes. In these environments a critical and elemental task consists of tracking multiple targets that are moving simultaneously. However, focusing on multiple moving targets is not trivial as it is very easy to lose continuity, particularly when the objects are situated within a very dense or cluttered background. While focus+context displays have been developed to improve users' ability to attend to important visual information, such techniques have not been applied to the visualization of moving objects. In this paper we evaluate the effectiveness of a focus+context technique, referred to as Semantic Depth of Field (SDOF), to the task of facilitating multiple target tracking. Results of our studies show an inclination for better performance with SDOF techniques, especially in low contrast scenarios.
机译:雷达控制系统和监控应用程序的用户必须不断从动态场景中提取基本信息。在这些环境中,关键和元素任务包括跟踪同时移动的多个目标。然而,专注于多个移动目标并不琐碎,因为它很容易失去连续性,特别是当物体位于非常密集或杂乱的背景内时。虽然已经开发了焦点+上下文显示以提高用户参加重要视觉信息的能力,但这些技术尚未应用于移动物体的可视化。在本文中,我们评估了焦点+上下文技术的有效性,称为字段(SDOF)的语义深度,以促进多个目标跟踪的任务。我们的研究结果表明,使用SDOF技术更好地表现出更好的性能,特别是在低对比度方案中。

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