Gianfranco Forlani

Complete classification of raw LIDAR data and 3D reconstruction of buildings

LIDAR (LIght Detection And Ranging) data are a primary data source for digital terrain model (DTM) generation and 3D city models. This paper presents a three-stage framework for a robust automatic classification of raw LIDAR data as buildings, ground and vegetation, followed by a reconstruction of 3D models of the buildings. In the first stage the raw data are filtered and interpolated over a grid. In the second stage, first a double raw data segmentation is performed and then geometric and topological relationships among regions resulting from segmentation are computed and stored in a knowledge base. In the third stage, a rule-based scheme is applied for the classification of the regions. Finally, polyhedral building models are reconstructed by analysing the topology of building outlines, building roof slopes and eaves lines. Results obtained on data sets with different ground point density, gathered over the town of Pavia (Italy) with Toposys and Optech airborne laser scanning systems, are shown to illustrate the effectiveness of the proposed approach.

Photogrammetry for geological applications: automatic retrieval of discontinuity orientation in rock slopes

The stability of a rock slope depends on the rock mass geo-structure and its discontinuities. Discontinuities show up at the rock surface as smooth and often plane surfaces. From their location and orientation the main families of fractures can be inferred and a stability analysis performed. To gather information on their distribution, surveys are typically carried out with geological compass and tape along scan lines, with obvious limitations and drawbacks. Here an highly automated image-based approach is presented to compute the required rock parameters: an accurate high resolution Digital Surface Model of the area of interest is generated from an image sequence and segmented in plane surfaces within a multi resolution RANSAC search, which returns location and orientation of each plane. To avoid measuring ground control points, the camera may be interfaced to a GPS receiver. Multiple overlapping and convergent images are captured to achieve good accuracy over the whole network, minimize occlusions and avoid poor object-camera relative geometry. The method is applied to the rock face of Corma di Machaby (Italy): the results are compared to those of a traditional survey with compass and to those of a laser scanner survey.

Testing Accuracy and Repeatability of UAV Blocks Oriented with GNSS-Supported Aerial Triangulation

UAV Photogrammetry today already enjoys a largely automated and efficient data processing pipeline. However, the goal of dispensing with Ground Control Points looks closer, as dual-frequency GNSS receivers are put on board. This paper reports on the accuracy in object space obtained by GNSS-supported orientation of four photogrammetric blocks, acquired by a senseFly eBee RTK and all flown according to the same flight plan at 80 m above ground over a test field. Differential corrections were sent to the eBee from a nearby ground station. Block orientation has been performed with three software packages: PhotoScan, Pix4D and MicMac. The influence on the checkpoint errors of the precision given to the projection centers has been studied: in most cases, values in Z are critical. Without GCP, the RTK solution consistently achieves a RMSE of about 2–3 cm on the horizontal coordinates of checkpoints. In elevation, the RMSE varies from flight to flight, from 2 to 10 cm. Using at least one GCP, with all packages and all test flights, the geocoding accuracy of GNSS-supported orientation is almost as good as that of a traditional GCP orientation in XY and only slightly worse in Z.

Photogrammetric bridging of GPS outages in mobile mapping

A photogrammetric strategy for the orientation of image sequences acquired by Mobile Mapping Vehicles (MMV) is presented. The motivations for this are twofold: to allow image georeferencing in short GPS outages for a MMV under development at the University of Parma, currently without an IMU; to improve the consistency of image georeferencing between asynchronous frames. The method may also contribute to limit the drift errors of low-cost integrated IMU/GPS systems in GPS outages. Drawing on techniques developed for Structure and Motion (S&M) reconstruction from image sequences and accounting for the specific conditions of the MMV imaging geometry, highly reliable multi-image matches are found, refining image orientation with a final bundle adjustment. Dealing with scenes containing poor image texture, the automation of the convergence of the bundle to the solution is still a problem. After a successful orientation of an image sequences of ca 70 m, the accuracy of the orientation and reconstruction process was checked in a test field by means of GPS observations and check points. Although not all constraints between synchronous image pairs are yet enforced, the accuracy degradation along the sequence was found to be still well within the specifications for the MMV.

Network Design and Quality Checks in Automatic Orientation of Close-Range Photogrammetric Blocks

Due to the recent improvements of automatic measurement procedures in photogrammetry, multi-view 3D reconstruction technologies are becoming a favourite survey tool. Rapidly widening structure-from-motion (SfM) software packages offer significantly easier image processing workflows than traditional photogrammetry packages. However, while most orientation and surface reconstruction strategies will almost always succeed in any given task, estimating the quality of the result is, to some extent, still an open issue. An assessment of the precision and reliability of block orientation is necessary and should be included in every processing pipeline. Such a need was clearly felt from the results of close-range photogrammetric surveys of in situ full-scale and laboratory-scale experiments. In order to study the impact of the block control and the camera network design on the block orientation accuracy, a series of Monte Carlo simulations was performed. Two image block configurations were investigated: a single pseudo-normal strip and a circular highly-convergent block. The influence of surveying and data processing choices, such as the number and accuracy of the ground control points, autofocus and camera calibration was investigated. The research highlights the most significant aspects and processes to be taken into account for adequate in situ and laboratory surveys, when modern SfM software packages are used, and evaluates their effect on the quality of the results of the surface reconstruction.

Where is photogrammetry heading to? State of the art and trends

The objective of this paper is to highlight current trends in photogrammetry, trying to foresee where they will lead the discipline in the next years. To this aim, first some remarks on the challenges brought to photogrammetry by other sensors and a brief historical survey of some research topics, where an increasing convergence between photogrammetry and computer vision is apparent, will be presented. Then, a necessarily concise review of the advances in automation in three basic photogrammetric tasks (namely image orientation, surface reconstruction and object restitution) will be illustrated. The purpose of the review is to highlight how the fruitful dialog between photogrammetry and computer vision led to today’s achievements and to point out what kind of approaches seem to be winning in the search for viable and robust solutions in the automation of processes. Finally, the conclusions will look at this convergence in the perspective of academic career.

Automatic extraction of LIDAR data classification rules

LIDAR (Light Detection And Ranging) data are a primary data source for digital terrain model (DTM) generation and 3D city models. This paper presents an AdaBoost algorithm for the identification of rules for the classification of raw LIDAR data mainly as buildings, ground and vegetation. First raw data are filtered, interpolated over a grid and segmented. Then geometric and topological relationships among regions resulting from segmentation constitute the input to the tree-structured classification algorithm. Results obtained on data sets gathered over the town of Pavia (Italy) are compared with those obtained by a rule-based approach previously presented by the authors for the classification of the regions.

Performance evaluation of DTM area-based matching reconstruction of Moon and Mars

High resolution DTMs, suitable for geomorphological studies of planets and asteroids, are today among the main scientific goals of space missions. In the framework of the BepiColombo mission, we are experimenting the use of different matching algorithms as well as the use of different geometric transformation models between stereo pairs, assessing their performances in terms of accuracy and computational efforts. Results obtained with our matching software are compared with those of established software. The comparison of the performance of image matching being the main objective of this work, all other steps of the DTM generation procedure have been made independent of the matching software by using a common framework. Tests with different transformation models have been performed using computer generated images as well as real HiRISE and LROC NAC images. The matching accuracy for real images has been checked in terms of reconstruction error against DTMs of Mars and the Moon published online and produced by the University of Arizona.

Innovative optical setup for testing a stereo camera for space applications

The Stereo Camera (STC) of the SIMBIO-SYS imaging suite of the BepiColombo ESA mission to Mercury is based on an innovative and compact design in which the light independently collected by two optical channels at ±20° separation with respect to nadir falls on a common bidimensional detector. STC adopts a novel stereo acquisition mode, based on the push-frame concept, never used before on a space mission. To characterize this camera for obtaining the most accurate data of the Mercury surface, standard calibration measurements have been performed. In addition, we also wanted to demonstrate and characterize the capability of the instrument to reconstruct a 3D surface with the desired accuracy by means of the stereo push-frame concept. To this end, a lab setup has been realized with an evaluation model of STC, in which the problem of working at an essentially infinite object distance over hundred km baselines has been overcome by means of a simple collimator and two precision rotators. The intrinsic and extrinsic parameters of the camera have been obtained with standard stereo procedures, adapted to the specific case. The stereo validation has been performed by comparing the shape of the target object accurately measured by laser scanning, with the shape reconstructed by applying the adopted stereo algorithm to the acquired image pairs. The obtained results show the goodness of this innovative validation technique, that will be applied also for validating the stereo capabilities of STC flight model.

Production of high-resolution digital terrain models in mountain regions to support risk assessment

Demand for high-accuracy digital terrain models (DTMs) in the Alpine region has been steadily increasing in recent years in valleys as well as high mountains. In the former, the determination of the geo-mechanical parameters of rock masses is the main objective; global warming, which causes the retreat of glaciers and the reduction of permafrost, is the main drive of the latter. The consequence is the instability of rock masses in high mountains: new cost-effective monitoring techniques are required to deal with the peculiar characteristics of such environment, delivering results at short notice. After discussing the design and execution of photogrammetric surveys in such areas, with particular reference to block orientation and block control, the paper describes the production of DTMs of rock faces and glacier fronts with light instrumentation and data acquisition techniques, allowing highly automated data processing. To this aim, the PhotoGPS technique and structure from motion algorithms are used to speed up the orientation process, while dense matching area-based correlation techniques are used to generate the DTMs.