| Summary: | 碩士 === 國立臺灣大學 === 土木工程學研究所 === 103 === Non-metric digital cameras have recently gained their increasing popularity in photogrammetric applications. To achieve quality performance of photogrammetric tasks, the estimation of camera parameters, among others, is of great concern. Camera calibration is designed to determine camera parameters, including interior orientation parameters and distortions, for effectively refining the image point so that object-to-image correspondence under collinearity property can be well justified. There are, however, some situations where camera calibration, especially for zoom-dependent cameras, is hard or impossible to operate, or the focal length employed in the site can not be fully preserved elsewhere, making camera calibration inapplicable or unreliable. Therefore, alternative ways of supplying camera parameters must be considered.
This research employed correction models, instead of actual calibration, to determine the camera parameters by referring to the recorded calibrated data sets of the very same camera on different principal distances. Two types of model have been formed. One features in estimating each kind of camera parameters in a separate fashion, while the other integrates all parameters and forms an effective polynomial function to estimate the overall amount of refinement. It is revealed from the experimental results that both models offer satisfactory estimations for image point refinement, especially when the quality of the calibrated data sets, the uncertainty of the focal distance of the target shown in metadata, and the best fitting order are taken into consideration through least-squares adjustment. Furthermore, the second model where the overall refinement is achieved by a single polynomial function gains better refinement than the first one, suggesting a convenient and sufficient alternative for image point refinement under no actual camera calibration.
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