Figure 5.

Robustness to dimensionality reduction. For each feature space, we reconstructed the feature matrix using a variable number of PCA components and then correlated the cosine distance in this feature space with the human scene distances. Although the number of features varies widely between spaces, all can be described in ~100 dimensions, and the ordering of how well the features predict human responses is essentially the same regardless of the number of original dimensions.