While reading canine facial expressions is vital for animal welfare, how head morphology affects human visual processing of dog faces remains under-researched. This study used eye-tracking technology to compare human visual attention when viewing domestic dogs with short-muzzled (brachycephalic) versus typical (normocephalic) facial structures. Participants allocated roughly 45% more visual attention to flat-faced dogs through repeated gazes rather than longer individual fixations, reflecting higher cognitive effort to decode compressed features. Although viewers fixated heavily on the ears of brachycephalic dogs, major discrepancies emerged between self-reported focus and objective gaze measurements. These findings demonstrate that altered facial structure complicates signal interpretation, highlighting important implications for veterinary practice and human-canine communication.
Prototype-based Explainable Deep Learning for Sex Classification of Mountain Gazelles in the Wild
Standard deep learning tools in automated wildlife monitoring often function
