Abstract:

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