ISSN 1671-3710
CN 11-4766/R

心理科学进展 ›› 2020, Vol. 28 ›› Issue (8): 1219-1231.doi: 10.3724/SP.J.1042.2020.01219

• 研究构想 •    下一篇


潘静(), 张慧远, 陈东濠, 徐宏格   

  1. 中山大学心理学系, 广州 510006
  • 收稿日期:2020-02-11 出版日期:2020-08-15 发布日期:2020-06-28
  • 通讯作者: 潘静
  • 基金资助:
    * 国家自然科学基金(319709882);广东省基础与应用基础研究基金(2020A1515010630);中山大学青年教师重点培养项目(19wkzd22)

Visual search in real world: The role of dynamic and static optical information

PAN Jing(), ZHANG Huiyuan, CHEN Donghao, XU Hongge   

  1. Department of Psychology, Sun Yat-sen University, Guangzhou 51006, China
  • Received:2020-02-11 Online:2020-08-15 Published:2020-06-28
  • Contact: PAN Jing


真实环境中的视觉搜索是人和动物赖以生存的重要能力。目前的视觉搜索研究多使用静态的观察者和静止的二维搜索对象, 侧重于探究注意在搜索中的作用; 现有的视觉搜索理论模型主要概括了影响搜索的自上而下的注意因素, 而将自下而上影响因素简单归结为影像显著性, 然而在真实环境中, 观察者或搜索对象是可以运动的, 搜索时可利用的视觉信息包括动态光流和静态影像结构信息。已有的视觉识别研究发现这两种信息相结合可以使观察者准确持久地识别场景、事件和三维结构。在现有视觉搜索理论模型中引入两种视觉信息可以较好还原真实环境中的搜索任务。我们提出研究构想和实验方案,探究利用动、静态视觉信息的视觉搜索过程, 从而完善现有的视觉搜索模型。我们认为充分利用环境信息可以提高搜索效率, 且在视觉搜索训练和智能搜索设计等方面有重要的应用价值。

关键词: 视觉搜索, 光流, 生物运动, 生态知觉理论


Visual search is a ubiquitous task and a critical skill for men and animals. Existing studies on visual search mainly focus on attentional guidance and the top-down cognitive influences on search effectiveness. The bottom-up influence on visual search is, rather crudely, simplified as objects’ image saliency. However, when searching in real world, where the observer and/or objects move, both static image information (the saliency of which has been considered in existing search models) and dynamic optic flow information are available. Optic flow is generated by the relative motions between an observer and world objects. So by detecting flow patterns, observers get to know the kinematic properties of events (which is defined as objects in motion) and hence perceive the physical properties of constituent objects, such as the mass, size and frictional coefficient etc.. These physical properties distinguish objects and allow the observer to search for a particular one. We integrate dynamical perceptual information (i.e. optic flow) into existing search models and in two studies, we test how combined dynamical and static perceptional information affect visual search for three-dimensional objects and for moving people, when the observer is stationary or moving. Furthermore, we attempt to develop a training protocol that improves search effectiveness in real world. Findings from this project will bring forth new theories for understanding visual search in real world, and have direct applications on personnel training and intelligent search designs.

Key words: visual search, optical flow, biological motion, ecological theory of perception