Steerable pyramid with subpixel compensation for remotely measuring and magnifying dynamic vibration of moving objects

Measuring vibration generated by a moving object is difficult because the accelerometers must be mounted on the moving object. Moreover, the weight and damping ratio of the accelerometers could cause extra mass and damping effect on small moving objects, casting doubt on the accuracy of such measurements. This paper reports a novel method that can remotely measure vibration from the motion of an object captured by a high-speed camera. Aimed at magnifying subtle changes in the presence of large motions, several phase-based video process methods have been proposed previously. Although these methods can capture such subtle changes, they all have deficiencies. For instance, the pure Euler method needs to process every position of movement, making the process very slow if the video file is large. Furthermore, the methods that combine Eulerian and Lagrangian algorithms ignore the subpixel compensation of stabilization. This paper reports a novel dynamic video processing technology by combining phase-based video process technology with visual tracking. The reason for using visual tracking is to extract the target and detect its dynamic position. To compensate for the error induced during the process of video stabilization, the steerable pyramid method was applied to enhance the magnification of subtle vibration with small error. The proposed method was verified by experiments to show that it can effectively improve the signal-to-noise ratio (SNR). The results demonstrated that the vibration and motion generated from the moving object can be detected and measured with satisfactory SNR. With the help of such an innovative method, in the future, both the motion and vibration signals of fast-moving objects, like airplanes, cars, or even small structures, can be measured simultaneously and remotely using high-speed cameras that can also move.