• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Intelligent Transportation Systems >Where Does the Driver Look? Top-Down-Based Saliency Detection in a Traffic Driving Environment
【24h】

Where Does the Driver Look? Top-Down-Based Saliency Detection in a Traffic Driving Environment

机译：驾驶员在哪里看？交通驾驶环境中基于自顶向下的显着性检测

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

A traffic driving environment is a complex and dynamically changing scene. When driving, drivers always allocate their attention to the most important and salient areas or targets. Traffic saliency detection, which computes the salient and prior areas or targets in a specific driving environment, is an indispensable part of intelligent transportation systems and could be useful in supporting autonomous driving, traffic sign detection, driving training, car collision warning, and other tasks. Recently, advances in visual attention models have provided substantial progress in describing eye movements over simple stimuli and tasks such as free viewing or visual search. However, to date, there exists no computational framework that can accurately mimic a driver's gaze behavior and saliency detection in a complex traffic driving environment. In this paper, we analyzed the eye-tracking data of 40 subjects consisted of nondrivers and experienced drivers when viewing 100 traffic images. We found that a driver's attention was mostly concentrated on the end of the road in front of the vehicle. We proposed that the vanishing point of the road can be regarded as valuable top-down guidance in a traffic saliency detection model. Subsequently, we build a framework of a classic bottom-up and top-down combined traffic saliency detection model. The results show that our proposed vanishing-point-based top-down model can effectively simulate a driver's attention areas in a driving environment.
机译：交通驾驶环境是一个复杂且动态变化的场景。驾驶时，驾驶员始终将注意力集中在最重要和最显着的区域或目标上。交通显着性检测可计算特定驾驶环境中的显着和先前区域或目标，是智能交通系统中必不可少的部分，可用于支持自动驾驶，交通标志检测，驾驶培训，汽车碰撞警告和其他任务。近来，视觉注意模型的进步已经在描述简单刺激和诸如自由观看或视觉搜索之类的任务的眼动方面提供了实质性进展。但是，迄今为止，还没有能够在复杂的交通驾驶环境中准确地模仿驾驶员的凝视行为和显着性检测的计算框架。在本文中，我们分析了观看100张交通图像时40位由非驾驶员和经验丰富的驾驶员组成的眼睛跟踪数据。我们发现，驾驶员的注意力主要集中在车辆前方的道路尽头。我们建议在交通显着性检测模型中，将道路的消失点视为有价值的自上而下的指导。随后，我们构建了一个经典的自下而上和自上而下的组合流量显着性检测模型的框架。结果表明，我们提出的基于消失点的自顶向下模型可以有效地模拟驾驶环境中驾驶员的注意力区域。

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