The view tolerance of human identity recognition depends on horizontal face information

Abstract

Abstract

Our ability to recognize objects and people across dramatic changes in physical appearance is a central yet unresolved question in vision science. In particular, the visual information that supports the human ability to recognize face identity across views is not fully specified. Past research suggests horizontally oriented face information plays a key role. To test this hypothesis, we investigated how humans use the visual information physically available across different orientation ranges of the face stimulus to recognize identity in a view-tolerant manner. Human observers performed an old/new identity recognition task with face stimuli presented under different viewpoints, achieved by rotating the faces in yaw (from left to right profile) and filtered to preserve contrast in selective orientation ranges. We found that human recognition performance remained tuned to the horizontal range of face information irrespective of yaw. We used a model observer approach to define the information physically available in the stimulus for matching face identity within each viewpoint (view-selective model observer) or across different viewpoints (view-tolerant model observer). The view-selective model indicated that face identity is carried by orientation ranges shifting from horizontal in frontal views to vertical in profile views. In contrast, the view-tolerant model showed that the horizontal range provides the most stable identity cues across views. The horizontally-tuned orientation profile of human recognition performance was predicted by the high diagnosticity of horizontal information in frontal views and the stability of the horizontal identity cues across views. The informativeness and stability of the identity cues carried by horizontal face information are confirmed by additional model observer evidence that this range best predicts the average summary of full-spectrum face appearances across views. Our findings indicate that the invariant representation of a face, gradually learned through repeated exposure to its natural appearance statistics, relies primarily on horizontal facial information. By identifying the spatial information supporting view-tolerant face recognition in humans, the present work yields concrete, data-driven constraints for the refinement of theoretical and computational models of visual recognition.