Sentence examples for motion SfM technique from inspiring English sources

Here, we propose a cost-effective, easily reproducible approach based on stereophotogrammetry and Structure from Motion (SfM) technique to study feedbacks between fluvial geomorphology and riparian vegetation at different nested spatiotemporal scales.

This method uses the Structure from Motion (SfM) technique to reconstruct a point cloud of the structures of the city, and matches the point cloud with the 3D building structures recovered from its 2D map.

We use Structure-from-Motion (SfM) techniques and archival aerial photos to quantify changes in sediment storage at the base of two major gully systems in recent decades.

On the other hand, 3D methods typically construct a three-dimensional model of the scene through structure-from-motion (SFM) techniques for smoothing motion [47], providing superior quality stabilization but at a higher computational cost [27, 47].

The main topographic information (Digital Surface Models, DSMs) was derived using an Unmanned Aerial Vehicle (UAV) and the Structure from Motion (SfM) photogrammetric technique.

Structure from motion (SfM) is a technique to estimate camera motion and 3D structure of the environment in a batch manner [24].

(Golparvar-Fard et al. 2011) used site photos to generate the point cloud, then match and pair the images to generate the as-planned and as-built models enabled by the technique of structure from motion (SfM).

Closely related photogrammetry techniques such as 'Structure from Motion' (SfM), an approach that allows 3D models to be reconstructed from overlapping images of a single moving camera, are also being employed to build high-resolution digital elevation terrains of such reefs17,18,19 and representations of single coral colonies at such fine resolutions that individual polyps can be reconstructed20.

The Structure from Motion (SfM), which is one of the 3D reconstruction techniques, is an important application of image matching.

By using computer vision techniques such as structure from motion (SfM), the location of photographers are estimated using the photographs captured in various illumination, resolution, zoom, and quality conditions (Golparvar-Fard et al. 2009b).

The several milestones leading to this progress are the automated interest points detection [2], the Structure from Motion (SfM) algorithms capable of reconstructing scenes from sets of unordered image collections [3, 4], and the dense image matching techniques delivering surface models of resolution equal to the pixel size on the ground [5, 6].