| Summary: | 碩士 === 國立中山大學 === 機械與機電工程學系研究所 === 94 === Abstract
In the researches of image tracking to restore an object’s position or velocity in the space, it is expectable that increasing numbers of camera can reduce the error. In fact, this phenomenon happens in practical applications. But so far, the physical theory behind this effect has not been fully known. Therefore, based on this motivation, this thesis tends to lay the physical foundation of specific machine vision problem using the statistical probability concept. Extensive error analysis and computer simulation for motion vector of translation movement solved by the least squares technique are conducted by incorporating Gaussian noised into optical flow components. It is expected to provide an effective theoretical model for further developments.
Keywords：Image tracking, The least squares method, Gauss distribution, Error
analysis.
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