Statistical analysis of different low cost GPS receivers for indoor and outdoor positioning

Piras, Marco; Marucco, Gianluca; Charqane, K.

doi:10.1109/plans.2010.5507325

Cited by 10 publications

(8 citation statements)

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“…Outdoors the GPS system can be sufficient to provide estimations of the device position (Piras et al, 2010), however indoors the GPS signal is usually not available (or not reliable). In order to allow position estimation in indoors conditions, the considered device is assumed to be provided of an INS based on embedded sensors as well: in particular, the considered smartphone is assumed to be provided of a 3-axis accelerometer and of a 3-axis magnetometer.…”

Section: System Descriptionmentioning

confidence: 99%

An ISVD-based Euclidian structure from motion for smartphones

Masiero

Guarnieri

Vettore

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The development of Mobile Mapping systems over the last decades allowed to quickly collect georeferenced spatial measurements by means of sensors mounted on mobile vehicles. Despite the large number of applications that can potentially take advantage of such systems, because of their cost their use is currently typically limited to certain specialized organizations, companies, and Universities. However, the recent worldwide diffusion of powerful mobile devices typically embedded with GPS, Inertial Navigation System (INS), and imaging sensors is enabling the development of small and compact mobile mapping systems. More specifically, this paper considers the development of a 3D reconstruction system based on photogrammetry methods for smartphones (or other similar mobile devices). The limited computational resources available in such systems and the users' request for real time reconstructions impose very stringent requirements on the computational burden of the 3D reconstruction procedure. This work takes advantage of certain recently developed mathematical tools (incremental singular value decomposition) and of photogrammetry techniques (structure from motion, Tomasi-Kanade factorization) to access very computationally efficient Euclidian 3D reconstruction of the scene. Furthermore, thanks to the presence of instrumentation for localization embedded in the device, the obtained 3D reconstruction can be properly georeferenced.

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Section: System Descriptionmentioning

confidence: 99%

An ISVD-based Euclidian structure from motion for smartphones

Masiero

Guarnieri

Vettore

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…accelerometer and magnetometer) allow the estimation of both the movements of the mobile device, and the attitude of the device during the camera shot. However, notice that, depending on the working conditions of interest, different choices can be considered without affecting the effectiveness of the procedure (Azizyan et al, 2009, Bahl and Padmanabhan, 2000, Cenedese et al, 2010, Foxlin, 2005, El-Sheimy et al, 2006, Lukianto and Sternberg, 2011, Ruiz et al, 2012, Youssef and Agrawala, 2005, Wang et al, 2012, Widyawan et al, 2012, Piras et al, 2010, Saeedi et al, 2014.…”

Section: System Descriptionmentioning

confidence: 99%

On the use of INS to improve Feature Matching

Masiero

Guarnieri

Vettore

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The continuous technological improvement of mobile devices opens the frontiers of Mobile Mapping systems to very compact systems, i.e. a smartphone or a tablet. This motivates the development of efficient 3D reconstruction techniques based on the sensors typically embedded in such devices, i.e. imaging sensors, GPS and Inertial Navigation System (INS). Such methods usually exploits photogrammetry techniques (structure from motion) to provide an estimation of the geometry of the scene. Actually, 3D reconstruction techniques (e.g. structure from motion) rely on use of features properly matched in different images to compute the 3D positions of objects by means of triangulation. Hence, correct feature matching is of fundamental importance to ensure good quality 3D reconstructions. Matching methods are based on the appearance of features, that can change as a consequence of variations of camera position and orientation, and environment illumination. For this reason, several methods have been developed in recent years in order to provide feature descriptors robust (ideally invariant) to such variations, e.g. Scale-Invariant Feature Transform (SIFT), Affine SIFT, Hessian affine and Harris affine detectors, Maximally Stable Extremal Regions (MSER). This work deals with the integration of information provided by the INS in the feature matching procedure: a previously developed navigation algorithm is used to constantly estimate the device position and orientation. Then, such information is exploited to estimate the transformation of feature regions between two camera views. This allows to compare regions from different images but associated to the same feature as seen by the same point of view, hence significantly easing the comparison of feature characteristics and, consequently, improving matching. SIFT-like descriptors are used in order to ensure good matching results in presence of illumination variations and to compensate the approximations related to the estimation process.

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“…In this case a GPS u-blox 6H has been embedded. The main performance of this GPS module are reported in Table 1 ( Piras et al, 2010).…”

Section: Microkopter Hexacopter Versionmentioning

confidence: 99%

Direct Photogrammetry Using Uav: Tests and First Results

Chiabrando

Lingua

Piras

2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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In recent years, the quality of high resolution acquisition platforms for geomatic applications has decidedly increased, especially in the performance of the sensors devoted to image acquisition.The small size of these new sensors combined with the increase in resolution allows them to be easily mounted onto Unmanned Aerial Vehicles (UAVs); in particular, calibrated, very-high-resolution digital cameras for photogrammetric purposes such as digital terrain model (DTM) and digital surface model (DSM) extraction, orthophotos, and map realization have been used. In this case, the UAV performance allows a high quality product to be obtained, considering the pixel size and the accuracy of the DTM/DSM which could be obtained with automatic procedures.Several navigation sensors (GPS/GNSS and IMU-MEMS) are embedded into UAVs in order to realize autonomous flight. The quality of these sensors, in terms of accuracy, depends on the model of UAV and its purpose. The navigation solution (position and attitude) is estimated by the internal UAV sensor and can be employed to directly georeference the images, in order to produce an quick and easy description and analysis of the overlooked area. This is a good condition for semi-automatic procedures using a bundle-block photogrammetric approach. But is it possible to realize a direct photogrammetry? And what are the limits?Several tests were carried out over different areas and in different conditions using three different UAVs belonging to the Geomatics group of the Politecnico di Torino.In this paper, an investigation of the limits of some commercial UAVs is reported, defining a dedicated procedure to valuate their performance, especially considering the use of UAVs for direct photogrammetry.

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Statistical analysis of different low cost GPS receivers for indoor and outdoor positioning

Cited by 10 publications

References 0 publications

An ISVD-based Euclidian structure from motion for smartphones

An ISVD-based Euclidian structure from motion for smartphones

On the use of INS to improve Feature Matching

Direct Photogrammetry Using Uav: Tests and First Results

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