Physiological studies have provided clear evidence of neurons sensitive to second-order motion, and first-order motion
mechanisms are blind to second-order motion. In this paper, we propose a computational simulation of second order
motion perception, which bases on energy-based detector with a preceded nonlinear process called texture grabber.
Generally, a texture grabber consists of a linear spatial filter, a linear temporal filter and a nonlinear transform, such as
full-wave rectification. Here Difference of Gaussians (DoG) functions are used as the spatial filters, and Difference of
Gammas (DoGamma) functions are chosen as the temporal filters. A series of experiments are computed and the results
confirm that our motion perception system detects second-order motion correctly.