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Specifically, as many cadastral boundaries coincide with visible boundaries, they could be extracted automatically using image analysis methods. Arguably, multiple parts of UAV-based cadastral mapping workflows could be automated. Existing procedures generally involve substantial fieldwork and many manual processes.

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The potential of high-resolution UAV imagery to create and update cadastral maps is being increasingly investigated. Geological Survey, Department of the Interior â€” The USGS Elevation Contours service from The National Map (TNM) consists of contours generated for the conterminous United States from 1- and 1/3 arc-second.Ĭontour Detection for UAV-Based Cadastral Mappingįull Text Available Unmanned aerial vehicles (UAVs provide a flexible and low-cost solution for the acquisition of high-resolution data. USGS Elevation Contours Overlay Map Service from The National Map The 2D estimate error is measured as on average between 2.4 and. In nearly 70% of all investigated video frames, a subjectively error free estimation could be achieved. The proposed algorithm was tested with head and shoulder video sequences (image resolution CIF. Exploiting knowledge about the position, a MAP estimator is developed taking into account the observed luminance gradient as well as a priori probabilities of chin and cheek contours positions.

Exploiting knowledge about the shape, a parametric 2D model representing chin and cheek contours is introduced. This algorithm exploits a priori knowledge about shape and position of chin and cheek contours in images. MAP Estimation of Chin and Cheek Contours in Video Sequencesĭirectory of Open Access Journals (Sweden)įull Text Available An algorithm for the estimation of chin and cheek contours in video sequences is proposed.

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