Abstract
In three experiments, we measured recognition as a function of exposure duration for three kinds of images of common objects: component images containing mainly low-spatial-frequency information, components containing mainly high-spatial-frequency information, and compound images created by summing the components. Our data were well fit by a model with a linear first stage in which the sums of the responses to the component images equalled the responses to the compound images. Our data were less well fit by a model in which the component responses combined by probability summation. These results support linear filter accounts of complex pattern recognition.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
