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- W2777984798 abstract "This study proposes a method for analysis and calibration of the geo-coding error in mapping of the moving targets, 'movers', detected in the Wide Area Motion Imagery (WAMI). To estimate the accurate position of the movers, an iterative Ordinary Least Squares (OLS) optimisation of the camera model parameters is performed. The OLS is set to minimise the Euclidean distance between the locations of the features projected from the camera frame and control points geo- referenced using Google Earth. A procedure for automated generation of visual features for camera calibration is proposed, alongside the manual procedure used for quality assessment of the results. A sequence of camera transformations used to map the features from the image frame is detailed as well as the iterative refinement to produce more accurate mapping. It is shown that iterative optimisation of the parameters underpinning the camera transformations from image to local navigational reference frames significantly improves the mapping accuracy, decreasing the position error from 58-100 m to 1-12 m for a set of reference points. The work also discusses the potential to apply developed camera calibration algorithms to each camera in the array, to correct the trajectories of the movers in the detected traffic flow across all frames." @default.
- W2777984798 created "2018-01-05" @default.
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- W2777984798 date "2017-11-01" @default.
- W2777984798 modified "2023-09-26" @default.
- W2777984798 title "Towards Automated Feature-Based Calibration of Wide-Area Motion Imagery" @default.
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- W2777984798 doi "https://doi.org/10.1109/dicta.2017.8227497" @default.
- W2777984798 hasPublicationYear "2017" @default.
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