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Jennifer L. Solberg, James M. Brown; Examining the Time Course of Ultra-Rapid Visual Categorization with Backward Masking. Journal of Vision 2004;4(8):880. doi: https://doi.org/10.1167/4.8.880.
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Research using ultra-rapid visual categorization (URVC) suggests observers are able to categorize photographs of natural scenes both accurately and quickly with extremely brief stimulus presentation times (~30 ms). Furthermore, results from these studies indicate URVC is the result of early stages of object recognition. The present study investigates the minimum exposure time needed to make rapid categorizations by combining the URVC paradigm with backward masking. In Experiment 1, categorization accuracy with briefly presented natural scenes is compared to performance when scenes are followed by a noise mask after a variable SOA. Experiment 2 compares URVC accuracy with photographs of natural scenes and line drawing renditions of the same scenes to test the hypothesis that early visual processing relies on a line drawing representation of the visual field, as suggested by models of object recognition (e.g., Biederman, 1987).
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