Cool. Newer way of testing foreground/background distinction for naturalistic images (as opposed to lines, sillhouettes, dots, etc).
In this, the texture details remain until V4 and LOC, rather than being processed away sooner.
“Background suppression in the human visual system. Correlation between brain activity and contrast, low- and high-pass filtering applied to the background (blue) and, as a control, to the foreground (red). Filled dots mark significant correlations (p < 0.05, Bonferroni corrected) while colored shaded areas represent the SE estimates. Dashed lines represent the SNR estimate for each ROI, while gray shaded regions indicate its SE. Arrows stand for significant differences (p < 0.05, Bonferroni corrected) between each filtering step and correlation values for the intact version (up: background suppression; down: progressive decay). Results show that for early regions (V1–V3) background-related information is relevant, since the correlation significantly decays due to filtering (p < 0.05, Bonferroni corrected); on the other hand, V4 and LOC show an opposite effect, suggesting that background is suppressed in those regions.”
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019392/
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Nice, they’re still processed early – under 150ms even though they get further refinement later.
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medial axis – saw a clever way to connect different layers through their medial axis – by computing the connection’s medial axis (stairs, ramp, etc) separately then bring it back to the others, overlapping it. Automating natural walking path.
https://www.youtube.com/watch?v=y8zV0pb3gKM
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