Abstract:Abstract. Nowadays time-of-flight (ToF) cameras and multiple RGB cameras are being embedded in an increasing number of high-end smartphones: despite their integration in mobile devices is mostly motivated by photographic applications, their availability can be exploited to enable 3D reconstructions directly on smartphones. Furthermore, even when a ToF camera is not embedded in a smartphone, low cost solutions are available on the market in order to easily provide standard mobile devices with a lightweight and … Show more
“…Time of Flight (ToF) and RGB images of a level of a building of the University of Padova (Fig. 1) have been collected and aligned by using a in-house simultaneous localization and mapping (SLAM, (Leonard and Durrant-Whyte, 1991)) approach (Masiero et al, 2020), based on the iterative match of visual features in the last two frames (Fig. 2).…”
Section: Data Acquisition Initial Alignment and Vertical Surface Detectionmentioning
Abstract. 3D building modeling is becoming an important support in civil engineering, architecture and cultural heritage applications. Despite static laser scanning can be considered as the state-of-the-art in such kind of applications, mobile mapping techniques can be considered as a suitable alternative to quickly gather geospatial information. Outdoor mobile mapping can be considered as a mature technique, which takes into advantage of the Global Navigation Satellite System (GNSS)-laser scanning information fusion. Instead, indoor mobile mapping is typically more challenging: the unavailability of GNSS makes the mapping system rely either just on the inertial navigation system, or on some control points. A drift in the navigation solution, and consequently in the 3D reconstruction, is typically visible after a while in the former case, whereas the use of other surveying instruments is required in the latter.This work aims at exploiting geometric characteristics of the buildings, such as symmetries and regularities, to reduce the drift effect in indoor mobile mapping, in particular when dealing with affordable systems. The proposed approach is based on the segmentation of the point clouds acquired with a time of flight camera (ToF), detecting in particular vertical planar surfaces. It is well known that aligning planar surfaces can be a viable way for reducing the drift in this kind of applications. Nevertheless, this paper aims also at investigating the use of geometric symmetries to such aim.The proposed approach is tested on a case study, a building of the University of Padova, whose reconstruction was produced by an ad hoc affordable mobile mapping system, integrating low cost inertial sensors, RGB and ToF camera.
“…Time of Flight (ToF) and RGB images of a level of a building of the University of Padova (Fig. 1) have been collected and aligned by using a in-house simultaneous localization and mapping (SLAM, (Leonard and Durrant-Whyte, 1991)) approach (Masiero et al, 2020), based on the iterative match of visual features in the last two frames (Fig. 2).…”
Section: Data Acquisition Initial Alignment and Vertical Surface Detectionmentioning
Abstract. 3D building modeling is becoming an important support in civil engineering, architecture and cultural heritage applications. Despite static laser scanning can be considered as the state-of-the-art in such kind of applications, mobile mapping techniques can be considered as a suitable alternative to quickly gather geospatial information. Outdoor mobile mapping can be considered as a mature technique, which takes into advantage of the Global Navigation Satellite System (GNSS)-laser scanning information fusion. Instead, indoor mobile mapping is typically more challenging: the unavailability of GNSS makes the mapping system rely either just on the inertial navigation system, or on some control points. A drift in the navigation solution, and consequently in the 3D reconstruction, is typically visible after a while in the former case, whereas the use of other surveying instruments is required in the latter.This work aims at exploiting geometric characteristics of the buildings, such as symmetries and regularities, to reduce the drift effect in indoor mobile mapping, in particular when dealing with affordable systems. The proposed approach is based on the segmentation of the point clouds acquired with a time of flight camera (ToF), detecting in particular vertical planar surfaces. It is well known that aligning planar surfaces can be a viable way for reducing the drift in this kind of applications. Nevertheless, this paper aims also at investigating the use of geometric symmetries to such aim.The proposed approach is tested on a case study, a building of the University of Padova, whose reconstruction was produced by an ad hoc affordable mobile mapping system, integrating low cost inertial sensors, RGB and ToF camera.
Abstract. Most of the high resolution topographic models are currently obtained either by means of Light Detection and Ranging (LiDAR) or photogrammetry: the former is usually preferred for producing very accurate models, whereas the latter is much more frequently used in low cost applications. In particular, the availability of more affordable Unmanned Aerial Vehicles (UAVs) equipped with high resolution cameras led to a dramatic worldwide increase of UAV photogrammetry-based 3D reconstructions. Nevertheless, accurate high resolution photogrammetric reconstructions typically require quite long data processing procedures, which make them less suitable for real-time applications.This work aims at investigating the use of a low cost Time of Flight (ToF) camera, combined with an Ultra-Wide Band (UWB) positioning system, mounted on a drone, in order to enable quasi real time 3D reconstructions of small to mid-size areas, even in locations where Global Navigation Satellite Systems (GNSSs) are not available.The proposed system, tested on a small area on the Italian Alps, provided high resolution mapping results, with an error of few centimeters with respect to a terrestrial close-range photogrammetry survey conducted on the same day.
Abstract. The increasing demand for reliable indoor navigation systems is leading the research community to investigate various approaches to obtain effective solutions usable with mobile devices. Among the recently proposed strategies, Ultra-Wide Band (UWB) positioning systems are worth to be mentioned because of their good performance in a wide range of operating conditions. However, such performance can be significantly degraded by large UWB range errors; mostly, due to non-line-of-sight (NLOS) measurements. This paper considers the integration of UWB with vision to support navigation and mapping applications. In particular, this work compares positioning results obtained with a simultaneous localization and mapping (SLAM) algorithm, exploiting a standard and a Time-of-Flight (ToF) camera, with those obtained with UWB, and then with the integration of UWB and vision. For the latter, a deep learning-based recognition approach was developed to detect UWB devices in camera frames. Such information is both introduced in the navigation algorithm and used to detect NLOS UWB measurements. The integration of this information allowed a 20% positioning error reduction in this case study.
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