This paper introduces a method of structural modal parameter identification based on visual vibrometry. For continuous and long time sampling video， this method ensures the accuracy and resolution of measurement results by setting local “virtual” measurement points and enlarging video slices， and significantly improves the data processing efficiency. It includes several steps： recording a video of the test structure under external excitations； Setting a series of “virtual measurement points” at the edge of the structure by using edge detection algorithm； Extracting apparent motions of “virtual measuring points” using optical flow methods， and then identifying natural frequencies and modal damping ratios using the stochastic subspace method； Estimating the full-field operational mode shapes of the structure by applying motion magnification to cropped videos. Two real-life tests are conducted to validate the procedure： firstly， vibration test of a model aircraft excited by a single sinusoidal input is used， where the response peak appears in the same frequency with the known-input. Secondly， operational modal analysis of a cantilevered beam is conduct‐ ed using visual vibrometry， in which the first five modal parameters are estimated and compared to the measurement results using a Scanning Laser Doppler Vibrometer. It is shown that the maximum relative discrepancies of the natural frequencies and damping ra‐ tios are only 0.35% and 14.6%， respectively， and the modal shapes are also observed in excellent correlation.