Suppr超能文献

呈现方式和深度单例在深度移动物体视觉搜索中的作用。

The role of presentation method and depth singletons in visual search for objects moving in depth.

作者信息

Finlayson Nonie J, Remington Roger W, Grove Philip M

机构信息

School of Psychology, The University of Queensland, St. Lucia, Queensland, Australia.

出版信息

J Vis. 2012 Aug 24;12(8):13. doi: 10.1167/12.8.13.

Abstract

Are objects moving in depth searched for efficiently? Previous studies have reported conflicting results, with some finding efficient search for only approaching motion (Franconeri & Simons, 2003), and others reporting that both approaching and receding motion are found more efficiently than static targets (Skarratt, Cole, & Gellatly, 2009). This may be due to presentation protocol differences and a confounding variable. We systematically tested the effect of the motion-in-depth presentation method and the effect of a confounding unique depth singleton on search performance. Simulating motion in depth using size scaling, changing binocular disparity, or a calibrated combination of these two depth cues, we found that search performance was affected by presentation method and that a combination of size scaling and changing disparity gives rise to the most compelling motion-in-depth perception. Exploiting this finding in Experiment 2, we found that removing the depth singleton does not affect motion-in-depth search performance. Overall, we found that search is more efficient for targets moving in depth than static targets. Approaching and receding motion had an equal advantage over static targets in target selection, shown through shallower search slopes. However, approaching motion had lower intercepts, consistent with an advantage over receding motion in later stages of processing associated with target identification and response.

摘要

在深度方向上移动的物体是否能被高效搜索?先前的研究报告了相互矛盾的结果,一些研究发现仅对接近运动能进行高效搜索(弗兰科内里和西蒙斯,2003年),而其他研究则报告称接近和后退运动都比静态目标更能被高效发现(斯卡拉特、科尔和盖拉特利,2009年)。这可能是由于呈现协议的差异以及一个混淆变量。我们系统地测试了深度运动呈现方法的效果以及一个混淆的独特深度单例对搜索性能的影响。通过使用大小缩放、改变双眼视差或这两种深度线索的校准组合来模拟深度运动,我们发现搜索性能受呈现方法影响,并且大小缩放和改变视差的组合会产生最引人注目的深度运动感知。在实验2中利用这一发现,我们发现去除深度单例不会影响深度运动搜索性能。总体而言,我们发现对于在深度方向上移动的目标的搜索比静态目标更高效。在目标选择方面,接近和后退运动相对于静态目标具有同等优势,这通过更浅的搜索斜率得以体现。然而,接近运动的截距更低,这与在与目标识别和反应相关的后期处理阶段相对于后退运动具有优势相一致。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验