Han Seohee, Rezanejad Morteza, Walther Dirk B
Department of Psychology, University of Toronto, 100 St. George Street, Toronto, Canada.
Mem Cognit. 2025 Jan;53(1):33-53. doi: 10.3758/s13421-023-01478-4. Epub 2023 Oct 30.
Why are some images more likely to be remembered than others? Previous work focused on the influence of global, low-level visual features as well as image content on memorability. To better understand the role of local, shape-based contours, we here investigate the memorability of photographs and line drawings of scenes. We find that the memorability of photographs and line drawings of the same scenes is correlated. We quantitatively measure the role of contour properties and their spatial relationships for scene memorability using a Random Forest analysis. To determine whether this relationship is merely correlational or if manipulating these contour properties causes images to be remembered better or worse, we split each line drawing into two half-images, one with high and the other with low predicted memorability according to the trained Random Forest model. In a new memorability experiment, we find that the half-images predicted to be more memorable were indeed remembered better, confirming a causal role of shape-based contour features, and, in particular, T junctions in scene memorability. We performed a categorization experiment on half-images to test for differential access to scene content. We found that half-images predicted to be more memorable were categorized more accurately. However, categorization accuracy for individual images was not correlated with their memorability. These results demonstrate that we can measure the contributions of individual contour properties to scene memorability and verify their causal involvement with targeted image manipulations, thereby bridging the gap between low-level features and scene semantics in our understanding of memorability.
为什么有些图像比其他图像更容易被记住?先前的研究主要关注全局、低层次视觉特征以及图像内容对记忆性的影响。为了更好地理解局部、基于形状的轮廓的作用,我们在此研究场景照片和线条图的记忆性。我们发现相同场景的照片和线条图的记忆性是相关的。我们使用随机森林分析定量测量轮廓属性及其空间关系对场景记忆性的作用。为了确定这种关系仅仅是相关性的,还是操纵这些轮廓属性会使图像被更好或更差地记住,我们将每张线条图分成两个半图像,根据训练好的随机森林模型,一个具有高预测记忆性,另一个具有低预测记忆性。在一项新的记忆性实验中,我们发现预测更易记忆的半图像确实被记得更好,证实了基于形状的轮廓特征,特别是T型交叉点在场景记忆性中的因果作用。我们对半图像进行了分类实验,以测试对场景内容的不同访问情况。我们发现预测更易记忆的半图像分类更准确。然而,单个图像的分类准确性与其记忆性不相关。这些结果表明,我们可以测量各个轮廓属性对场景记忆性的贡献,并通过有针对性的图像操作验证它们的因果关系,从而在我们对记忆性的理解中弥合低层次特征与场景语义之间的差距。