Predicting where people look in natural scenes has attracted a lot of interest in computer vision and computational neuroscience over the past two decades. Two seemingly contrasting categories of cues have been proposed to influence where people look: \textit{low-level image saliency} and \textit{high-level semantic information}. Our first contribution is to take a detailed look at these cues to confirm the hypothesis proposed by Henderson~\cite{henderson1993eye} and Nuthmann \& Henderson~\cite{nuthmann2010object} that observers tend to look at the center of objects. We analyzed fixation data for scene free-viewing over 17 observers on 60 fully annotated images with various types of objects. Images contained different types of scenes, such as natural scenes, line drawings, and 3D rendered scenes. Our second contribution is to propose a simple combined model of low-level saliency and object center-bias that outperforms each individual component significantly over our data, as well as on the OSIE dataset by Xu et al.~\cite{xu2014predicting}. The results reconcile saliency with object center-bias hypotheses and highlight that both types of cues are important in guiding fixations. Our work opens new directions to understand strategies that humans use in observing scenes and objects, and demonstrates the construction of combined models of low-level saliency and high-level object-based information.

研究自然场景中人们的注意力转移，在低层图像显著性和高层语义信息等方面提出了两个看似相互矛盾的提示，其中分析了物体中心偏置的影响，并提出了一种结合低层视觉显著性和物体中心偏置的模型，旨在深入了解人类在观察场景和对象时使用的策略，并展示结合低层视觉显著性和高层物体信息的模型的构建。

对解释自由观察注视时显着性和物体中心偏倚假设的调和