Natural scene statistics predict how humans pool information across space in surface tilt estimation
Fig 9
Estimation error of adaptive elliptical pooling model.
A The adaptive elliptical pooling areas dictated by target tilt. B The relative elliptical pooling area for different target tilts. As the average equivalent diameter increases or decreases, the relative sizes of the pooling area remain in a fixed proportion. C Estimation error (model estimate vs. groundtruth tilt) as a function of equivalent diameter. The insets show simulation results that compare performance of the adaptive elliptical pooling model vs. the fixed circular pooling model on 1000 matched randomly sampled stimulus sets. Computing the estimation errors on matched stimulus sets isolates the impact of the model, and prevents stimulus variability from unduly affecting the results. The adaptive pooling model (blue) outperforms the fixed circular pooling model (black) on nearly all stimulus sets (i.e., data is below positive diagonal). D Simulation results, just as in C insets, except that estimation error is shown as a function of groundtruth tilt (subpanels). The fact that the majority of points lie below the dashed unity line, indicates that adaptive elliptical pooling outperforms fixed circular pooling in groundtruth tilt estimation at all groundtruth tilts.