Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2011 Sep 12;6(9):e24038. doi: 10.1371/journal.pone.0024038

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

Wilming et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

PMC Copyright notice

All data shown are AUC values averaged over all predictions of single subjects on single images in a given parameter combination. The predictions are based on a spatial bias (large matrix, ‘Subject and Image independent’), a subject-specific bias (column next to the matrix, ‘Subject-specific’), a PCA-cleaned subject-specific bias (rightmost column), an image-specific bias (row above the matrix, ‘Image-specific’, also referred to as inter-subject consistency) and the combination of image and subject-specific bias (topmost row). The ‘Subject and Image independent’ scores depend on the number of subjects and images used for the prediction and represent a lower bound for fixation selection models. The ‘Image-specific’ scores also depend on the number of images and yield an upper bound for fixation selection models. Comparing ‘Subject-specific’ and Subject and Image independent reveals the effect of using a subject-specific bias. The dashed lines indicate at what subject group size the subject-specific bias stops being significantly better than the spatial bias (paired t-test, ). The subject-specific bias is not significantly different from the spatial bias between the dashed and solid lines. See main text for more detailed descriptions.

Inline graphic — All data shown are AUC values averaged over all predictions of single subjects on single images in a given parameter combination. The predictions are based on a spatial bias (large matrix, ‘Subject and Image independent’), a subject-specific bias (column next to the matrix, ‘Subject-specific’), a PCA-cleaned subject-specific bias (rightmost column), an image-specific bias (row above the matrix, ‘Image-specific’, also referred to as inter-subject consistency) and the combination of image and subject-specific bias (topmost row). The ‘Subject and Image independent’ scores depend on the number of subjects and images used for the prediction and represent a lower bound for fixation selection models. The ‘Image-specific’ scores also depend on the number of images and yield an upper bound for fixation selection models. Comparing ‘Subject-specific’ and Subject and Image independent reveals the effect of using a subject-specific bias. The dashed lines indicate at what subject group size the subject-specific bias stops being significantly better than the spatial bias (paired t-test, ). The subject-specific bias is not significantly different from the spatial bias between the dashed and solid lines. See main text for more detailed descriptions.