Conjugate imagery in the automated reproduction of three dimensional coordinates from two dimensional coordinate data

The three-dimensional video analysis of human motion commonly utilises automated image processing and digitisation processes to produce real-time unidentified two-dimensional coordinate data of segmental markers. In what can be a time-consuming process the two-dimensional data are then identified and tracked to produce three-dimensional coordinates. This paper presents an approach to the automated reproduction of three-dimensional coordinates from two-dimensional coordinate data. Conjugate imaging techniques were utilised in the development of four criterion measures for determining the validity of conjugate (corresponding) image points. An algorithm based on the criterion measures was then developed for the automated reproduction of three dimensional coordinates from camera image coordinate data. The algorithm was tested with a 55 point marker system viewed in four video cameras (digitisation error approx. 0.2%, lab point separation ≥ 6 cm). The success of the algorithm was dependent on the closeness of markers, the accuracy of the photogrammetric system, and the number of markers visible in two camera images. The present research has developed techniques based on conjugate imagery for the automated reproduction of three-dimensional coordinates from two-dimensional data, and provided a bases for further development of automated three-dimensional tracking.