This project focuses on the development and characterization of a high speed video motion capture system for the measurement of planar, rigid body motions. The ability to collect information related to the accelerations, velocities and positions of points on a rigid body as it moves in planar space is very important in the fields of science and engineering. Traditional techniques, including the use of accelerometers, extensors and lasers, either rely on contact between the rigid body and the sensor or only measure out of plane motion. In this project, an inexpensive monochromatic high speed camera was used in conjunction with markers adhered to the objects under investigation to measure the planar displacement of a point on a moving object. The high speed camera is able to capture video at a rate of up to 20,000 frames per second, however, at this speed the field of view is very small. For a larger field of view, the frames per second is diminished to close to 3,000 frames per second.

The goal of this project was to develop the hardware parameters and software necessary to collect and process 2D motion data at different frequencies and then evaluate the efficacy of video motion capture through comparison with simultaneously captured acceleration data. The efficacy was evaluated over a range of accelerations using variable frequency oscillations. The video footage was processed, frame by frame in order to extract x and y position for the center of the marker. Extraction of the position data was completed using the MATLAB computer vision toolbox, which provides tools for identifying the x and y locations of corners, circle centers and other defining features.

The project began by identifying size, shape, color and material of markers for effective data collection using the motion capture system. Additionally, camera settings, field of view, capture rate, lighting and mounting conditions were evaluated to determine what conditions would result in the most accurate position sensing. In order to validate the measurements from the motion capture system, position data were correlated with accelerations measured from a traditional accelerometer located on the object under test. In order for the position data collected through the high speed video capture to be compared with the acceleration data collected using measurement from accelerometers, numerical differentiation of the position signals gathered from the high speed footage was performed. The efficacy of different shape and size markers, along with other camera settings, will be demonstrated for specific oscillatory test profiles.

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