A multi-frame approach to visual motion perception

UAV-Borne Mapping Algorithms for Low-Altitude and High-Speed Drone Applications

This article presents an analysis of current state-of-the-art sensors and how these sensors work with several mapping algorithms for UAV (Unmanned Aerial Vehicle) applications, focusing on low-altitude and high-speed scenarios. A new experimental construct is created using highly realistic environments made possible by integrating the AirSim simulator with Google 3D maps models using the Cesium Tiles plugin. Experiments are conducted in this high-realism simulated environment to evaluate the performance of three distinct mapping algorithms: (1) Direct Sparse Odometry (DSO), (2) Stereo DSO (SDSO), and (3) DSO Lite (DSOL). Experimental results evaluate algorithms based on their measured geometric accuracy and computational speed. The results provide valuable insights into the strengths and limitations of each algorithm. Findings quantify compromises in UAV algorithm selection, allowing researchers to find the mapping solution best suited to their application, which often requires a compromise between computational performance and the density and accuracy of geometric map estimates. Results indicate that for UAVs with restrictive computing resources, DSOL is the best option. For systems with payload capacity and modest compute resources, SDSO is the best option. If only one camera is available, DSO is the option to choose for applications that require dense mapping results.

Hazard Assessment of Rocky Slopes: An Integrated Photogrammetry–GIS Approach Including Fracture Density and Probability of Failure Data

Natural rock slopes require accurate engineering–geological characterization to determine their stability conditions. Given that a natural rock mass is often characterized by a non-uniform fracture distribution, the correct, detailed, and accurate characterization of the discontinuity pattern of the rock mass is essential. This is crucial, for example, for identifying the possibility and the probability of kinematic releases. In addition, complete stability analyses of possible rockfall events should be performed and used to create hazard maps capable of identifying the most dangerous parts of a rock mass. This paper shows a working approach that combines traditional geological surveys and remote sensing techniques for engineering–geological investigations in a natural rock slope in Northern Italy. Discontinuities were identified and mapped in a deterministic way by using semi-automatic procedures that were based on detailed 3D Unmanned Aerial Vehicle photogrammetric-based point cloud data and provided georeferenced representations of thousands of fractures. In this way, detailed documentation of the geo-mechanical and geo-structural characteristics of discontinuities were obtained and subsequently used to create fracture density maps. Then, traditional kinematic analyses and probabilistic stability analyses were performed using limit equilibrium methods. The results were then managed in a GIS environment to create a final hazard map that classifies different portions of the rock slope based on three factors: kinematic predisposition to rockfall (planar sliding, wedge sliding, toppling), fracture density, and probability of failure. The integration of the three hazard factors allowed the identification of the most hazardous areas through a deterministic and accurate procedure, with a high level of reliability. The adopted approach can therefore be very useful to determine the areas in which to prioritize remediation measures with the aim of reducing the level of risk.

Analysis of Sea Storm Events in the Mediterranean Sea: The Case Study of 28 December 2020 Sea Storm in the Gulf of Naples, Italy

The coastline of the Gulf of Naples, Italy, is characterized by a series of infrastructures of strategic importance, including touristic and commercial ports between Pozzuoli to Sorrento, main roads, railways, and urban areas. Furthermore, the Gulf of Naples hosts an intense traffic of touristic and commercial maritime routes. The risk associated with extreme marine events is hence very significant over this marine and coastal area. On 28 December 2020, the Gulf of Naples was hit by an extreme sea storm, with severe consequences. This study focuses on the waterfront area of Via Partenope, where the waves overrun the roadway, causing massive damage on coastal seawall, road edges, and touristic structures (primarily restaurants). Based on the analysis of the meteorological evolution of the sea storm and its effects on the waterfront, we suggest that reflective processes induced on the sea waves by the tuff cliffs at the base of Castel dell’Ovo had an impact in enhancing the local-scale waves magnitude. This caused in turn severe flooding of the roadway and produced widespread damage along the coast. The analysis of the event of 28 December 2020, also suggests the need of an effective mitigation policy in the management of coastal issues induced by extreme sea storm events. Wind-based analysis and prediction of the sea wave conditions are currently discussed in the literature; however, critical information on wave height is often missing or not sufficient for reliable forecasting. In order to improve our ability to forecast the effects of sea storm events on the coastline, it is necessary to analyze all the components of the coastal wave system, including wave diffraction and reflection phenomena and the tidal change. Our results suggest in fact that only an integrated approach to the analysis of all the physical and anthropic components of coastal system may provide a correct base of information for the stakeholders to address coastal zone planning and protection.

Assessment of DSM Based on Radiometric Transformation of UAV Data

Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 m and UAV Drone data from 300 and 500 m flying height. RAW UAV images acquired from 500 m flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 m flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 m flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 m to ±0.11 m. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.

Monitoring of Strain and Temperature in an Open Pit Using Brillouin Distributed Optical Fiber Sensors

Marble quarries are quite dangerous environments in which rock falls may occur. As many workers operate in these sites, it is necessary to deal with the matter of safety at work, checking and monitoring the stability conditions of the rock mass. In this paper, some results of an innovative analysis method are shown. It is based on the combination of Distributed Optical Fiber Sensors (DOFS), digital photogrammetry through Unmanned Aerial Vehicle (UAV), topographic, and geotechnical monitoring systems. Although DOFS are currently widely used for studying infrastructures, buildings and landslides, their use in rock marble quarries represents an element of peculiarity. The complex morphologies and the intense temperature range that characterize this environment make this application original. The selected test site is the Lorano open pit which is located in the Apuan Alps (Italy); here, a monitoring system consisting of extensometers, crackmeters, clinometers and a Robotic Total Station has been operating since 2012. From DOFS measurements, strain and temperature values were obtained and validated with displacement data from topographic and geotechnical instruments. These results may provide useful fundamental indications about the rock mass stability for the safety at work and the long-term planning of mining activities.

SfM-MVS Photogrammetry for Rockfall Analysis and Hazard Assessment Along the Ancient Roman Via Flaminia Road at the Furlo Gorge (Italy)

Rockfall events represent significant hazards for areas characterized by high and steep slopes and therefore effective mitigation controls are essential to control their effect. There are a lot of examples all over the world of anthropic areas at risk because of their proximity to a rock slope. A rockfall runout analysis is a typical 3D problem, but for many years, because of the lack of specific software, powerful computers, and economic reasons, a 2D approach was normally adopted. However, in recent years the use of 3D software has become quite widespread and different runout working approaches have been developed. The contribution and potential use of photogrammetry in this context is undoubtedly great. This paper describes the application of a 3D hybrid working approach, which considers the integrated use of traditional geological methods, Terrestrial Laser Scanning, and drone based Digital Photogrammetry. Such approach was undertaken in order to perform the study of rockfall runout and geological hazard in a natural slope in Italy in correspondence of an archaeological area. Results show the rockfall hazard in the study area and highlights the importance of using photogrammetry for the correct and complete geometrical reconstruction of slope, joints, and block geometries, which is essential for the analysis and design of proper remediation measures.

Analysis by UAV Digital Photogrammetry of Folds and Related Fractures in the Monte Antola Flysch Formation (Ponte Organasco, Italy)

The deformation structures (folds and fractures) affecting Monte Antola flysch formation in the area of Ponte Organasco (Northern Apennines-Italy) were analyzed by Unmanned Aerial Vehicle Digital Photogrammetry (UAVDP). This technique allowed the realization of Digital Outcrop Models (DOMs) interpreted in a stereoscopic environment by collecting a large number of digital structural measures (strata, fractures and successively fold axes and axial planes). In particular, by UAVDP was possible to analyze the relationships between folds and fractures all along the study structures. The structural analysis revealed the presence of a series of NE-vergent folds characterized by a typical Apenninic trend and affected by four main sets of fractures. Fractures are always sub-orthogonal to the bedding, maintains constant angular relationships with the bedding and seems linked to the folding deformation. The study shows that the UAVDP technique can overcome the main limitations of field structural analysis such as the scarce presence and the inaccessibility (total or partial) of rock outcrops and allows for acquiring images of rock outcrops at a detailed scale from user-inaccessible positions and different points of view and analyze inaccessible parts of outcrops.

Noise causes slant underestimation in stereo and motion

This paper discusses a problem, which is inherent in the estimation of 3D shape (surface normals) from multiple views. Noise in the image signal causes bias, which may result in substantial errors in the parameter estimation. The bias predicts the underestimation of slant found in psychophysical and computational experiments. Specifically, we analyze the estimation of 3D shape from motion and stereo using orientation disparity. For the case of stereo, we show that bias predicts the anisotropy in the perception of horizontal and vertical slant. For the case of 3D motion we demonstrate the bias by means of a new illusory display. Finally, we discuss statistically optimal strategies for the problem and suggest possible avenues for visual systems to deal with the bias.

Three-dimensional modeling from two-dimensional video

This paper presents the surface-based factorization method to recover three-dimensional (3-D) structure, i.e., the 3-D shape and 3-D motion, of a rigid object from a two-dimensional (2-D) video sequence. The main ingredients of our approach are as follows: 1) we describe the unknown shape of the 3-D rigid object by polynomial patches; 2) projections of these patches in the image plane move according to parametric 2-D motion models; 3) we recover the parameters describing the 3-D shape and 3-D motion from the 2-D motion parameters by factorizing a matrix that is rank 1 in a noiseless situation. Our method is simultaneously an extension and a simplification of the original factorization method of Tomasi and Kanade (1992). We track regions where the 2-D motion in the image plane is described by a single set of parameters, avoiding the need to track a large number of pointwise features, in general, a difficult task. Then our method estimates the parameters describing the 3-D structure by factoring a rank 1 matrix, not rank 3 as in Tomasi and Kanade. This allows the use of fast iterative algorithms to compute the 3-D structure that best fits the data. Experimental results with real-life video sequences illustrate the good performance of our approach.