A Correspondence Framework for ALS Strip Adjustments based on Variants of the ICP Algorithm

Glira, Philipp; Pfeifer, Norbert; Briese, Christian; Ressl, Camillo

doi:10.1127/pfg/2015/0270

Cited by 96 publications

(84 citation statements)

References 8 publications

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“…The concept consists of searching for the nearest pairs of points from two data sets and then minimizing the distance between them, in the iterative adjustment process (Eggert and Daylot, 2012). Such an approach can be performed with respect to ALS strip adjustments (Glira et al, 2015). One point cloud is considered as the reference cloud and the second cloud is matched to the first one.…”

Section: The Proposed Methodology Of Data Acquisition and Processingmentioning

confidence: 99%

Possibilities for Using Lidar and Photogrammetric Data Obtained With an Unmanned Aerial Vehicle for Levee Monitoring

Bakuła

Ostrowski

Szender³

et al. 2016

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

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Commission I, ICWG I/VbKEY WORDS: UAV, UAS, LiDAR, ultra-light, accuracy, DTM ABSTRACT:This paper presents the possibilities for using an unmanned aerial system for evaluation of the condition of levees. The unmanned aerial system is equipped with two types of sensor. One is an ultra-light laser scanner, integrated with a GNSS receiver and an INS system; the other sensor is a digital camera that acquires data with stereoscopic coverage. Sensors have been mounted on the multirotor, unmanned platform the Hawk Moth, constructed by MSP company. LiDAR data and images of levees the length of several hundred metres were acquired during testing of the platform. Flights were performed in several variants. Control points measured with the use of the GNSS technique were considered as reference data. The obtained results are presented in this paper; the methodology of processing the acquired LiDAR data, which increase in accuracy when low accuracy of the navigation systems occurs as a result of systematic errors, is also discussed. The Iterative Closest Point (ICP) algorithm, as well as measurements of control points, were used to georeference the LiDAR data. Final accuracy in the order of centimetres was obtained for generation of the digital terrain model. The final products of the proposed UAV data processing are digital elevation models, an orthophotomap and colour point clouds. The authors conclude that such a platform offers wide possibilities for low-budget flights to deliver the data, which may compete with typical direct surveying measurements performed during monitoring of such objects. However, the biggest advantage is the density and continuity of data, which allows for detection of changes in objects being monitored.

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Section: The Proposed Methodology Of Data Acquisition and Processingmentioning

confidence: 99%

Possibilities for Using Lidar and Photogrammetric Data Obtained With an Unmanned Aerial Vehicle for Levee Monitoring

Bakuła

Ostrowski

Szender³

et al. 2016

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

View full text Add to dashboard Cite

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“…Respective discrepancies are detected within standard quality control procedures (Ressl et al, 2008). If the deviations exceed acceptable limits, a typical LiDAR workflow also includes an adjustment to minimize the offsets between the strips (Glira et al, 2015a).…”

Section: Lidar Workflowmentioning

confidence: 99%

“…Thorough orientation of overlapping LiDAR strips and images, respectively, is a precondition for high-quality surface reconstruction. Sophisticated flight block orientation strategies and software implementations exist for both ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-2/W4, 2017 ISPRS Geospatial Week 2017, 18-22 September 2017, Wuhan, China laser scans (Skaloud and Lichti, 2006;Glira et al, 2015a) and images (Kraus, 2007;Förstner and Wrobel, 2016). However, the simultaneous use of data from LiDAR and image matching implies a second level of relative orientation between scans and images which is important to consider when jointly using the point clouds of both acquisition techniques for deriving products (surface and terrain models, orthophoto mosaics, etc.).…”

Section: Introductionmentioning

confidence: 99%

Improved Topographic Models via Concurrent Airborne Lidar And Dense Image Matching

Mandlburger

Wenzel²,

Spitzer

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Modern airborne sensors integrate laser scanners and digital cameras for capturing topographic data at high spatial resolution. The capability of penetrating vegetation through small openings in the foliage and the high ranging precision in the cm range have made airborne LiDAR the prime terrain acquisition technique. In the recent years dense image matching evolved rapidly and outperforms laser scanning meanwhile in terms of the achievable spatial resolution of the derived surface models. In our contribution we analyze the inherent properties and review the typical processing chains of both acquisition techniques. In addition, we present potential synergies of jointly processing image and laser data with emphasis on sensor orientation and point cloud fusion for digital surface model derivation. Test data were concurrently acquired with the RIEGL LMS-Q1560 sensor over the city of Melk, Austria, in January 2016 and served as basis for testing innovative processing strategies. We demonstrate that (i) systematic effects in the resulting scanned and matched 3D point clouds can be minimized based on a hybrid orientation procedure, (ii) systematic differences of the individual point clouds are observable at penetrable, vegetated surfaces due to the different measurement principles, and (iii) improved digital surface models can be derived combining the higher density of the matching point cloud and the higher reliability of LiDAR point clouds, especially in the narrow alleys and courtyards of the study site, a medieval city.

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“…To solve this shift error, we used the TLS point cloud to co-register the photogrammetric point cloud using the ICP algorithm and to extract the coordinates of some natural features employed as GCPs for combining direct geo-referencing with GCPs method. A version of the ICP algorithm tailored to topographic point clouds (Glira et al, 2015) was applied. The coregistration with the TLS point cloud minimized the orientation error of the photogrammetric model.…”

Section: Accuracy Assessment Regarding To the Geo-referencing Approachmentioning

confidence: 99%

Panorama Image Sets for Terrestrial Photogrammetric Surveys

Piermattei

Karel

Vettore

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:High resolution 3D models produced from photographs acquired with consumer-grade cameras are becoming increasingly common in the fields of geosciences. However, the quality of an image-based 3D model depends on the planning of the photogrammetric surveys. This means that the geometric configuration of the multi-view camera network and the control data have to be designed in accordance with the required accuracy, resolution and completeness. From a practical application point of view, a proper planning (of both photos and control data) of the photogrammetric survey especially for terrestrial acquisition, is not always ensured due to limited accessibility of the target object and the presence of occlusions. To solve these problems, we propose a different image acquisition strategy and we test different geo-referencing scenarios to deal with the practical issues of a terrestrial photogrammetric survey. The proposed photogrammetric survey procedure is based on the acquisition of a sequence of images in panorama mode by rotating the camera on a standard tripod. The offset of the pivot point from the projection center prevents the stitching of these images into a panorama. We demonstrate how to still take advantage of this capturing mode. The geo-referencing investigation consists of testing the use of directly observed coordinates of the camera positions, different ground control point (GCP) configurations, and GCPs with different accuracies, i.e. artificial targets vs. natural features. Images of the test field in a low-slope hill were acquired from the ground using an SLR camera. To validate the photogrammetric results a terrestrial laser scanner survey is used as benchmark.

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A Correspondence Framework for ALS Strip Adjustments based on Variants of the ICP Algorithm

Cited by 96 publications

References 8 publications

Possibilities for Using Lidar and Photogrammetric Data Obtained With an Unmanned Aerial Vehicle for Levee Monitoring

Possibilities for Using Lidar and Photogrammetric Data Obtained With an Unmanned Aerial Vehicle for Levee Monitoring

Improved Topographic Models via Concurrent Airborne Lidar And Dense Image Matching

Panorama Image Sets for Terrestrial Photogrammetric Surveys

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