Allocentric and egocentric cues constitute an internal reference frame for real-world visual search

Visual search in natural environments involves numerous objects, each composed of countless features. Despite this complexity, our brain efficiently locates targets. Here, we propose that the brain combines multiple reference cues to form an internal reference frame that facilitates real-world visual search. Objects in natural scenes often appear in orientations perceived as upright, enabling quicker recognition. However, how object orientation influences real-world visual search remains unknown. Moreover, the contributions of different reference cues--egocentric, visual context, and gravitational-- are not well understood. To answer these questions, we designed a visual search task in virtual reality. Our results revealed an orientation effect independent of set size, suggesting reference frame transformation rather than object rotation. By rotating virtual scenes and participants in a flight simulator, we found that allocentric cues drastically altered search performance. These findings provide novel insights into the efficiency of real-world visual search and its connection to multimodal cognition. SignificanceA central question in the behavioral sciences concerns how people efficiently perceive natural environments. Visual search exemplifies this challenge. While research has elucidated the basic mechanisms, traditional theories struggle to explain the remarkable efficiency in real-world scenes. Here, we examine a fundamental property of natural scenes: reference frames. Real-world objects typically appear in consistent orientations, suggesting that orientation may guide search. Yet, the influence of object orientation on real-world search--and which reference cues (egocentric, visual context, or gravitational) determine that orientation--remains unknown. We developed a novel virtual-reality paradigm to address these questions. We demonstrated that humans combine multiple reference cues to form an internal reference frame that guides visual search, providing a novel account of the efficiency of real-world search.