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Faces and text attract gaze independent of the task: Experimental data and computer model
 

Summary: Faces and text attract gaze independent of the task:
Experimental data and computer model
Computation and Neural Systems,
California Institute of Technology, Pasadena, CA, USAMoran Cerf
Computation and Neural Systems,
California Institute of Technology, Pasadena, CA, USAE. Paxon Frady
Computation and Neural Systems,
California Institute of Technology, Pasadena, CA, USA, &
Department of Brain and Cognitive Engineering,
Korea University, Seoul, KoreaChristof Koch
Previous studies of eye gaze have shown that when looking at images containing human faces, observers tend to rapidly
focus on the facial regions. But is this true of other high-level image features as well? We here investigate the extent to
which natural scenes containing faces, text elements, and cell phonesVas a suitable controlVattract attention by tracking
the eye movements of subjects in two types of tasksVfree viewing and search. We observed that subjects in free-viewing
conditions look at faces and text 16.6 and 11.1 times more than similar regions normalized for size and position of the face
and text. In terms of attracting gaze, text is almost as effective as faces. Furthermore, it is difficult to avoid looking at faces
and text even when doing so imposes a cost. We also found that subjects took longer in making their initial saccade when
they were told to avoid faces/text and their saccades landed on a non-face/non-text object. We refine a well-known bottom­up
computer model of saliency-driven attention that includes conspicuity maps for color, orientation, and intensity by adding
high-level semantic information (i.e., the location of faces or text) and demonstrate that this significantly improves the

  

Source: Adolphs, Ralph - Psychology and Neuroscience, California Institute of Technology
Koch, Christof - Division of Biology, California Institute of Technology

 

Collections: Biology and Medicine