Development of Aerial Stiv Applied to Videotated Movie From Multicopter Based on High-Accurate Image Stabilization

Abstract

In recent years, the so-called unmanned air vehicles (UAV), remotely controlled airplanes or multicopters, have become available for various civil engineering purposes. In the field of river engineering, although they have been used to investigate the area of vegetation zone or other objectives, measurement of river flow has not been conducted by using an UAV, probably due to the difficulty of image stabilization. In this research, we developed a method to measure river surface velocity distributions by using videotaped images. The specific feature of the method is the introduction of a high-accurate and efficient image stabilization in order to apply the space-time image velocimetry (STIV) to airborne images. The developed method was applied to investigate snowmelt flood of the Uono River, with success of measuring twodimensional velocity distributions for a river reach of about four hundred meters. The obtained results were used to compare with those measured by ADCP or STIV using oblique images from a riverbank.

Velocity Vector Estimation of Two-Dimensional Flow Field Based on STIV

“…For non-contact flow measurement techniques, the representative ones are Acoustic Doppler Current Profiler (ADCP) [ 2 ], particle image velocimetry (PIV) [ 3 ], large-scale particle image velocimetry (LSPIV) [ 4 ], feature matching velocimetry (FMV) [ 5 ], optical flow (OF) [ 6 ], and space-time image velocimetry (STIV) [ 7 , 8 , 9 , 10 , 11 ], the last five of which is river surface image velocimetry that uses the movement of artificially added tracer particles or visible "natural" features on the water surface (e.g., eddies, ripples, or other floats) to achieve non-contact measurement of surface velocity distributions. Surface velocity data can be gathered for extended periods of time using image-based velocimetry without the need for hydrographic workers to be on duty.…”

Airborne Feature Matching Velocimetry for surface flow measurements in rivers

“…Points of typical characteristic features like edges, corners, blobs, or ridges can be determined by, e.g. Scale-Invariant-Feature-Transform (SIFT) of Lowe (2004), as applied in Fujita et al (2015), or by Speeded Up Robust Features (SURF) of Bay et al (2006), as used in Detert and Weitbrecht (2015). However, developments in computer vision resulted in further feature point detection techniques, such as Oriented FAST and Rotated BRIEF (ORB, by Rublee et al, 2011), or KAZE (Japanese for "wind", by Alcantarilla et al, 2012).…”