LAUSR

A normally sighted person can see a grating of 30 cycles per degree or higher, but spatial frequencies needed for motion perception are much lower than that. It is unknown for natural images with a wide spectrum how all the visible spatial frequencies contribute to motion speed perception. In this work, we studied the effect of spatial frequency content on motion speed estimation for sequences of natural and stochastic pixel images by simulating different visual conditions, including normal vision, low vision (low-pass filtering), and complementary vision (high-pass filtering at the same cutoff frequencies of the corresponding low-vision conditions) conditions. Speed was computed using a biological motion energy-based computational model. In natural sequences, there was no difference in speed estimation error between normal vision and low vision conditions, but it was significantly higher for complementary vision conditions (containing only high-frequency components) at higher speeds. In stochastic sequences that had a flat frequency distribution, the error in normal vision condition was significantly larger compared with low vision conditions at high speeds. On the contrary, such a detrimental effect on speed estimation accuracy was not found for low spatial frequencies. The simulation results were consistent with the motion direction detection task performed by human observers viewing stochastic sequences. Together, these results (i) reiterate the importance of low frequencies in motion perception, and (ii) indicate that high frequencies may be detrimental for speed estimation when low frequency content is weak or not present.