We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.

https://cyberleninka.org/article/n/529930.pdf

Unmanned aerial systems for photogrammetry and remote sensing: A review

Unmanned aerial vehicle (UAV) platforms are nowadays a valuable source of data for inspection, surveillance, mapping, and 3D modeling issues. As UAVs can be considered as a low-cost alternative to the classical manned aerial photogrammetry, new applications in the short- and close-range domain are introduced. Rotary or fixed-wing UAVs, capable of performing the photogrammetric data acquisition with amateur or SLR digital cameras, can fly in manual, semiautomated, and autonomous modes. Following a typical photogrammetric workflow, 3D results like digital surface or terrain models, contours, textured 3D models, vector information, etc. can be produced, even on large areas. The paper reports the state of the art of UAV for geomatics applications, giving an overview of different UAV platforms, applications, and case studies, showing also the latest developments of UAV image processing. New perspectives are also addressed.

UAV for 3D mapping applications: a review

The invention is directed to an apparatus for use in a transluminal procedure. The apparatus, comprising, for example, a housing having a guide lumen and a seal proximal to a distal end of the housing that extends across and completely seals the guide lumen; a fixation element in the housing and adapted to secure the distal end of the housing to tissue; and a channel extending through the side wall of the housing having an outlet in communication with the lumen distal of the seal. Methods are also provided. For example, a method includes, performing a transluminal procedure by: securing a datum and position indicator to a wall of a target lumen; forming an opening in the wall; advancing an instrument through the opening; and tracking the advancement of the instrument using the datum and position indicator.

Methods and apparatus for performing transluminal and other procedures

A steerable, tendon-driven endoscope is described herein. The endoscope has an elongated body with a manually or selectively steerable distal portion and an automatically controlled, segmented proximal portion. The steerable distal portion and the segment of the controllable portion are actuated by at least two tendons. As the endoscope is advanced, the user maneuvers the distal portion, and a motion controller actuates tendons in the segmented proximal portion so that the proximal portion assumes the selected curve of the selectively steerable distal portion. By this method the selected curves are propagated along the endoscope body so that the endoscope largely conforms to the pathway selected. When the endoscope is withdrawn proximally, the selected curves can propagate distally along the endoscope body. This allows the endoscope to negotiate tortuous curves along a desired path through or around and between organs within the body.

Tendon-driven endoscope and methods of insertion

An electro-polymeric articulated endoscope and method of insertion are described herein. A steerable endoscope having a segmented, elongated body with a manually or selectively steerable distal portion and an automatically controlled proximal portion can be articulated by electro-polymeric materials. These materials are configured to mechanically contract or expand in the presence of a stimulus, such as an electrical field. Adjacent segments of the endoscope can be articulated using the electro-polymeric material by inducing relative differences in size or length of the material when placed near or around the outer periphery along a portion of the endoscope.

Activated polymer articulated instruments and methods of insertion

The initial steps of many computer vision algorithms are interest point extraction and matching. In larger image sets the pairwise matching of interest point descriptors between images is an important bottleneck. For each descriptor in one image the (approximate) nearest neighbor in the other one has to be found and checked against the second-nearest neighbor to ensure the correspondence is unambiguous. Here, we asked the question how to best decimate the list of interest points without losing matches, i.e. we aim to speed up matching by filtering out, in advance, those points which would not survive the matching stage. It turns out that the best filtering criterion is not the response of the interest point detector, which in fact is not surprising: the goal of detection are repeatable and well-localized points, whereas the objective of the selection are points whose descriptors can be matched successfully. We show that one can in fact learn to predict which descriptors are matchable, and thus reduce the number of interest points significantly without losing too many matches. We show that this strategy, as simple as it is, greatly improves the matching success with the same number of points per image. Moreover, we embed the prediction in a state-of-the-art Structure-from-Motion pipeline and demonstrate that it also outperforms other selection methods at system level.

Predicting Matchability

Estimating a depth map from multiple views of a scene is a fundamental task in computer vision. As soon as more than two viewpoints are available, one faces the very basic question how to measure similarity across >2 image patches. Surprisingly, no direct solution exists, instead it is common to fall back to more or less robust averaging of two-view similarities. Encouraged by the success of machine learning, and in particular convolutional neural networks, we propose to learn a matching function which directly maps multiple image patches to a scalar similarity score. Experiments on several multi-view datasets demonstrate that this approach has advantages over methods based on pairwise patch similarity.

Learned Multi-patch Similarity

Feature matching – i.e. finding corresponding point features in different images to serve as tie-points for camera orientation – is a fundamental step in photogrammetric 3D reconstruction. If the input image set is large and unordered, which is becoming increasingly common with the spread of photogrammetric recording to untrained user groups and even crowd-sourced geodata collection, the bottleneck of the reconstruction pipeline is the matching step, for two reasons. (i) Image acquisition without detailed viewpoint planning requires a denser set of viewpoints with larger overlaps, to ensure appropriate coverage of the object of interest and to guarantee sufficient redundancy for reliable reconstruction in spite of the unoptimised network geometry. As a consequence, there is a large number of images with overlapping viewfields, resulting in a more expensive matching step than, say, a regular block geometry. (ii) In the absence of a carefully pre-planned recording sequence it is not even known which images overlap. One thus faces the even bigger challenge to determine which pairs of images even can have tie-points and should therefore be fed into the matching procedure. In this paper we attempt a systematic survey of the state-of-the-art for tie-point generation in unordered image collections, including recent developments for very large image sets.

Recent developments in large-scale tie-point matching

A device for infrared (IR) spectroscopic investigation of internal surfaces of a body, for example of blood vessels, comprising an endoscope (10) with light guide means to illuminate the surfaces is characterized in that at the distal end of the light guide means there is arranged a detector (12) for detecting IR light scattered from the illuminated surface and transforming it into electric signals. For otherwise identical conditions, compared to comparable known devices, the device according to the invention offers a higher signal strength and thereby the possibility to shorten the measuring time for equal signal quality.

Device for infrared (IR) spectroscopic investigations of internal surfaces of a body

. If images acquired from Unmanned Aerial Vehicles (UAVs) need to be accurately geo-referenced, the method of choice is classical aerotriangulation, since on-board sensors are usually not accurate enough for direct geo-referencing. For several different applications it has recently been proposed to mount thermal cameras on UAVs. Compared to optical images, thermal ones pose a number of challenges, in particular low resolution and weak local contrast. In this work we investigate the automatic orientation of thermal image blocks acquired from a UAV, using artificial ground control points. To that end we adapt the photogrammetric processing pipeline to thermal imagery. The pipeline achieves accuracies of about ±1 cm in planimetry and ±3 cm in height for the object points, respectively ±10 cm or better for the camera positions, compared to ±100 cm or worse for direct geo-referencing using on-board single-frequency GPS.

/pdf/determination-of-the-uav-position-by-automatic-processing-of-5ftzl0oaz9.pdf

Wilfried Hartmann

Papers

Predicting Matchability

Learned Multi-patch Similarity

Recent developments in large-scale tie-point matching

Device for infrared (IR) spectroscopic investigations of internal surfaces of a body

Determination of the uav position by automatic processing of thermal images