ISSN : 1226-9654
Human visual system represents a statistical summary of a complex visual input to overcome its limited capacity. An example of summary representation is the average size perception, which has been known to be accurate and precise. In the current study, we developed and validated a computational model of mean size perception. In this model, we assumed that the visual system encodes individual sizes with early noise, then integrates the noisy size information from multiple inputs. Finally, the integrated size information is added by late noise. The suggested model was validated with a psychophysical experiment, in which the standard and the test displays included multiple circles with different sizes and observers were asked to report which display had larger mean size. The psychophysical data was well accounted by the model with late noise: threshold for mean size discrimination was decreased with set-size, but the decrement of threshold was decelerated in large set-sizes. The proposed model allows us to understand underlying mechanism of mean size perception, and the experimental paradigm used in the current study is expected to be a useful tool for studying ensemble perception of various visual properties.
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