Diagnostic spatial frequencies and human efficiency for discriminating actions

Humans extract visual information from the world through spatial frequency (SF) channels that are sensitive to different scales of light-dark fluctuations across visual space. Using two methods, we measured human SF tuning for discriminating videos of human actions (walking, running, skipping and jumping). The first, more traditional, approach measured signal-to-noise ratio (s/n) thresholds for videos filtered by one of six Gaussian band-pass filters ranging from 4 to 128 cycles/image. The second approach used SF “bubbles”, Willenbockel et al. (Journal of Experimental Psychology. Human Perception and Performance, 36(1), 122–135, 2010), which randomly filters the entire SF domain on each trial and uses reverse correlation to estimate SF tuning. Results from both methods were consistent and revealed a diagnostic SF band centered between 12-16 cycles/image (about 1-1.25 cycles/body width). Efficiency on this task was estimated by comparing s/n thresholds for humans to an ideal observer, and was estimated to be quite low (>.04%) for both experiments.