Reconstructing complex structures from planar cross-sections is a challenging problem, with wide-reaching applications in medical imaging, manufacturing, and topography. Out-of-the-box point cloud reconstruction methods can often fail due to the data sparsity between slicing planes, while current bespoke methods struggle to reconstruct thin geometric structures and preserve topological continuity. This is important for medical applications where thin vessel structures are present in CT and MRI scans. This paper introduces CrossSDF, a novel approach for extracting a 3D signed distance field from 2D signed distances generated from planar contours. Our approach makes the training of neural SDFs contour-aware by using losses designed for the case where geometry is known within 2D slices. Our results demonstrate a significant improvement over existing methods, effectively reconstructing thin structures and producing accurate 3D models without the interpolation artifacts or over-smoothing of prior approaches.

Powerline inspection is an important task for electric power management. Corridor mapping, i.e., the task of surveying the surroundings of the line and detecting potentially hazardous vegetation and objects, is performed by aerial light detection and ranging (LiDAR) survey. To this purpose, the main tasks are automatic extraction of the wires and measurement of the distance of objects close to the line. In this article, we present a new fully automated solution, which does not use time-consuming line fitting method, but is based on simple geometrical assumptions and relies on the fact that wire points are isolated, sparse and widely separated from all other points in the data set. In particular, we detect and classify pylons by local-maxima strategy. Then, a new reference system, having its origin on the first pylon and y-axis toward the second one, is defined. In this new reference system, transverse sections of the raw point cloud are extracted; by iterating such procedure for all detected pylons, we are able to detect the wire bundle. Obstacles are then automatically detected according to corridor mapping requirements. The algorithm is tested on two relevant data sets.

In this work a new lightweight LiDAR solution designed for UAV application will be investigated. In particular, we show that using this multi-echo LiDAR it is possible to obtain DTM reconstruction of the densely forested area surveyed in good agreement with the local technical regional map (CTR). We have also estimated the mean height of the trees from the estimated CHM with relative error equal to 5%.

In this work we evaluate the performance of UAV-based photogrammetry for 3D building modeling, by comparison with ground LiDAR data. In particular we show that accuracy of the photogrammetric model is in the order of 0.1m globally, and better than 0.05m for local measurements.

Experimental validation is presented, for a new active infrared technique previously proposed by the authors for detecting shallowly buried low-metal-content landmines, based on infrared heaters and low-cost sensors. After a heating phase, temperature anomaly is observed at soil surface during cooling, due to different heat diffusivity of mine materials with respect to the ground. We define two possible landmine presence indicators, namely temperature contrast and cooling rate. Reported results of experiments in dry and moist soil confirm simulations, proving that reliable detection is feasible within 3-5 cm depth, and that dynamical detection performs better, at the price of more repeated measurements.

This paper presents an application of the European Remote Sensing (ERS) satellites' radar data to digital elevation model (DEM) generation. The selected test site is the Sannio-Matese area in southern Italy, where several corner reflectors (CRs) were deployed to be used as ground control points (GCPs) for height measurement accuracy validation. First of all, an analysis of the CR response in radar images is presented. Then, the procedure for image pair geometric registration and interferogram formation is described in detail. A quantitative analysis is also performed by comparing these interferograms to the corresponding products obtained by using the ISAR software, officially distributed by the European Space Agency (ESA). Reported correlation values show that only tandem pairs allow an efficient interferometric processing to be performed, thanks to their short-time baseline (one day), whereas correlation adequate for differential interferometry could not be achieved. The method adopted for the computation of the interferometric baseline components on the basis of satellite orbital data is described, including the GCP-based corrections. The procedure was applied to obtain DEMs of a 10/spl times/10 km/sup 2/ subarea characterized by very high correlation coefficients (0.6). The best attained values of the GCP height measurement accuracy were about 4 m. Finally, the DEMs were compared, giving root mean square (rms) differences less than 20 m in the best case.