isprsannals II 3 W2 37 2013
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The proposed algorithm for building extraction in airborne LiDAR data can be divided into three key steps: Filtering, scan line segmentation, object based classification.. 2.1
experience, different and not consistent results can be obtained using the same image dataset but importing images in a different sequence order. Since photogrammetry
Tracking comparison between the proposed method (top) and KLT (bottom) shows a significant tracking improvement on this aerial dataset, especially along image borders where the
The original images with the input Stixels (left), the 2D mapping results overlaid on Google Earth images (center) and the 3D representation (right) using the OctoMap representation
Once the features of the basic pitched roof component are recognized (top left), the feature recognition will work on the grey (sub-surface) segment (top middle) with the
In this paper we develop and compare two methods for scene classification in 3D object space, that is, not single image pixels get classified, but voxels which carry geometric,
(2008) calculated a single spatial probability distribution from mobile phone data using a statistical approach and determined that 'inherent similarity in travel
The GeoVideo data are divided into moving trajectory and video segments around the monitoring object and the same time period video segments from different
