Reppa Irene, Greville W James, Leek E Charles
a Department of Psychology, Wales Institute for Cognitive Neuroscience , Swansea University , Swansea , UK.
b Wolfson Centre for Clinical and Cognitive Neuroscience, School of Psychology , Bangor University , Bangor , UK.
Q J Exp Psychol (Hove). 2015;68(12):2351-69. doi: 10.1080/17470218.2015.1014379. Epub 2015 Mar 13.
This study contrasted the role of surfaces and volumetric shape primitives in three-dimensional object recognition. Observers (N = 50) matched subsets of closed contour fragments, surfaces, or volumetric parts to whole novel objects during a whole-part matching task. Three factors were further manipulated: part viewpoint (either same or different between component parts and whole objects), surface occlusion (comparison parts contained either visible surfaces only, or a surface that was fully or partially occluded in the whole object), and target-distractor similarity. Similarity was varied in terms of systematic variation in nonaccidental (NAP) or metric (MP) properties of individual parts. Analysis of sensitivity (d') showed a whole-part matching advantage for surface-based parts and volumes over closed contour fragments--but no benefit for volumetric parts over surfaces. We also found a performance cost in matching volumetric parts to wholes when the volumes showed surfaces that were occluded in the whole object. The same pattern was found for both same and different viewpoints, and regardless of target-distractor similarity. These findings challenge models in which recognition is mediated by volumetric part-based shape representations. Instead, we argue that the results are consistent with a surface-based model of high-level shape representation for recognition.
本研究对比了表面和体积形状基元在三维物体识别中的作用。观察者（N = 50）在一个整体-部分匹配任务中，将封闭轮廓片段、表面或体积部分的子集与全新的整体物体进行匹配。进一步操纵了三个因素：部分视角（组成部分与整体物体之间的视角相同或不同）、表面遮挡（比较部分仅包含可见表面，或者在整体物体中有一个完全或部分被遮挡的表面）以及目标-干扰项相似度。相似度根据各个部分的非偶然（NAP）或度量（MP）属性的系统变化而变化。敏感性分析（d'）表明，基于表面的部分和体积在整体-部分匹配方面优于封闭轮廓片段——但体积部分相对于表面并无优势。我们还发现，当体积显示出在整体物体中被遮挡的表面时，将体积部分与整体进行匹配会出现性能成本。对于相同和不同的视角，以及无论目标-干扰项相似度如何，都发现了相同的模式。这些发现对那些认为识别由基于体积部分的形状表征介导的模型提出了挑战。相反，我们认为这些结果与用于识别的基于表面的高级形状表征模型是一致的。
