scholarly journals THE POSSIBILITY OF USING IMAGES OBTAINED FROM THE UAS IN CADASTRAL WORKS

2016 ◽  
Vol XLI-B1 ◽  
pp. 909-915 ◽  
Author(s):  
Z. Kurczynski ◽  
K. Bakuła ◽  
M. Karabin ◽  
M. Kowalczyk ◽  
J. S. Markiewicz ◽  
...  
Keyword(s):  
Image Matching ◽  
Bundle Adjustment ◽  
Aerial Photographs ◽  
Surface Model ◽  
Digital Surface Model ◽  
Reference Field ◽  
Alternative Source ◽  
Dense Image ◽  
Low Altitude ◽  
Very High

Updating the cadastre requires much work carried out by surveying companies in countries that have still not solved the problem of updating the cadastral data. In terms of the required precision, these works are among the most accurate. This raises the question: to what extent may modern digital photogrammetric methods be useful in this process? The capabilities of photogrammetry have increased significantly after the introduction of digital aerial cameras and digital technologies. For the registration of cadastral objects, i.e., land parcels’ boundaries and the outlines of buildings, very high-resolution aerial photographs can be used. The paper relates an attempt to use an alternative source of data for this task - the development of images acquired from UAS platforms. Multivariate mapping of cadastral parcels was implemented to determine the scope of the suitability of low altitude photos for the cadastre. In this study, images obtained from UAS with the GSD of 3 cm were collected for an area of a few square kilometres. Bundle adjustment of these data was processed with sub-pixel accuracy. This led to photogrammetric measurements being carried out and the provision of an orthophotomap (orthogonalized with a digital surface model from dense image matching of UAS images). Geometric data related to buildings were collected with two methods: stereoscopic and multi-photo measurements. Data related to parcels’ boundaries were measured with monoplotting on an orthophotomap from low-altitude images. As reference field surveying data were used. The paper shows the potential and limits of the use of UAS in a process of updating cadastral data. It also gives recommendations when performing photogrammetric missions and presents the possible accuracy of this type of work.

scholarly journals THE POSSIBILITY OF USING IMAGES OBTAINED FROM THE UAS IN CADASTRAL WORKS

2016 ◽  
Vol XLI-B1 ◽  
pp. 909-915
Author(s):  
Z. Kurczynski ◽  
K. Bakuła ◽  
M. Karabin ◽  
M. Kowalczyk ◽  
J. S. Markiewicz ◽  
...  
Keyword(s):  
Image Matching ◽  
Bundle Adjustment ◽  
Aerial Photographs ◽  
Surface Model ◽  
Digital Surface Model ◽  
Reference Field ◽  
Alternative Source ◽  
Dense Image ◽  
Low Altitude ◽  
Very High

Updating the cadastre requires much work carried out by surveying companies in countries that have still not solved the problem of updating the cadastral data. In terms of the required precision, these works are among the most accurate. This raises the question: to what extent may modern digital photogrammetric methods be useful in this process? The capabilities of photogrammetry have increased significantly after the introduction of digital aerial cameras and digital technologies. For the registration of cadastral objects, i.e., land parcels’ boundaries and the outlines of buildings, very high-resolution aerial photographs can be used. The paper relates an attempt to use an alternative source of data for this task - the development of images acquired from UAS platforms. Multivariate mapping of cadastral parcels was implemented to determine the scope of the suitability of low altitude photos for the cadastre. In this study, images obtained from UAS with the GSD of 3 cm were collected for an area of a few square kilometres. Bundle adjustment of these data was processed with sub-pixel accuracy. This led to photogrammetric measurements being carried out and the provision of an orthophotomap (orthogonalized with a digital surface model from dense image matching of UAS images). Geometric data related to buildings were collected with two methods: stereoscopic and multi-photo measurements. Data related to parcels’ boundaries were measured with monoplotting on an orthophotomap from low-altitude images. As reference field surveying data were used. The paper shows the potential and limits of the use of UAS in a process of updating cadastral data. It also gives recommendations when performing photogrammetric missions and presents the possible accuracy of this type of work.

scholarly journals UNSUPERVISED MULTI-CONSTRAINT DEEP NEURAL NETWORK FOR DENSE IMAGE MATCHING

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 163-167
Author(s):  
W. Yuan ◽  
Z. Fan ◽  
X. Yuan ◽  
J. Gong ◽  
R. Shibasaki
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Image Matching ◽  
Deep Neural Network ◽  
Aerial Images ◽  
Surface Model ◽  
Learning Technology ◽  
Ground Sample ◽  
Volume Calculation ◽  
Dense Image

Abstract. Dense image matching is essential to photogrammetry applications, including Digital Surface Model (DSM) generation, three dimensional (3D) reconstruction, and object detection and recognition. The development of an efficient and robust method for dense image matching has been one of the technical challenges due to high variations in illumination and ground features of aerial images of large areas. Nowadays, due to the development of deep learning technology, deep neural network-based algorithms outperform traditional methods on a variety of tasks such as object detection, semantic segmentation and stereo matching. The proposed network includes cost-volume computation, cost-volume aggregation, and disparity prediction. It starts with a pre-trained VGG-16 network as a backend and using the U-net architecture with nine layers for feature map extraction and a correlation layer for cost volume calculation, after that a guided filter based cost aggregation is adopted for cost volume filtering and finally the soft Argmax function is utilized for disparity prediction. The experimental conducted on a UAV dataset demonstrated that the proposed method achieved the RMSE (root mean square error) of the reprojection error better than 1 pixel in image coordinate and in-ground positioning accuracy within 2.5 ground sample distance. The comparison experiments on KITTI 2015 dataset shows the proposed unsupervised method even comparably with other supervised methods.

scholarly journals Digital Surface Model Interpolation Based on 3D Mesh Models

2018 ◽  
Vol 11 (1) ◽  
pp. 24 ◽  
Author(s):  
Soohyeon Kim ◽  
Sooahm Rhee ◽  
Taejung Kim
Keyword(s):  
Image Matching ◽  
3D Visualization ◽  
Interpolation Method ◽  
Stereo Image ◽  
Distribution Model ◽  
Surface Model ◽  
Digital Surface Model ◽  
3D Mesh ◽  
Stereo Image Matching ◽  
Mesh Models

A digital surface model (DSM) is an important geospatial infrastructure used in various fields. In this paper, we deal with how to improve the quality of DSMs generated from stereo image matching. During stereo image matching, there are outliers due to mismatches, and non-matching regions due to match failure. Such outliers and non-matching regions have to be corrected accurately and efficiently for high-quality DSM generation. This process has been performed by applying a local distribution model, such as inverse distance weight (IDW), or by forming a triangulated irregular network (TIN). However, if the area of non-matching regions is large, it is not trivial to interpolate elevation values using neighboring cells. In this study, we proposed a new DSM interpolation method using a 3D mesh model, which is more robust to outliers and large holes. We compared mesh-based DSM with IDW-based DSM and analyzed the characteristics of each. The accuracy of the mesh-based DSM was a 2.80 m root mean square error (RMSE), while that for the IDW-based DSM was 3.22 m. While the mesh-based DSM successfully removed empty grid cells and outliers, the IDW-based DSM had sharper object boundaries. Because of the nature of surface reconstruction, object boundaries appeared smoother on the mesh-based DSM. We further propose a method of integrating the two DSMs. The integrated DSM maintains the sharpness of object boundaries without significant accuracy degradation. The contribution of this paper is the use of 3D mesh models (which have mainly been used for 3D visualization) for efficient removal of outliers and non-matching regions without a priori knowledge of surface types.

scholarly journals 3D RECONSTRUCTION WITH A COLLABORATIVE APPROACH BASED ON SMARTPHONES AND A CLOUD-BASED SERVER

2017 ◽  
Vol XLII-2/W8 ◽  
pp. 187-194 ◽  
Author(s):  
E. Nocerino ◽  
F. Poiesi ◽  
A. Locher ◽  
Y. T. Tefera ◽  
F. Remondino ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Image Matching ◽  
Point Cloud ◽  
Point Clouds ◽  
Bundle Adjustment ◽  
Collaborative Approach ◽  
Matching Algorithm ◽  
Dense Image ◽  
Video Feed ◽  
And Performance

The paper presents a collaborative image-based 3D reconstruction pipeline to perform image acquisition with a smartphone and geometric 3D reconstruction on a server during concurrent or disjoint acquisition sessions. Images are selected from the video feed of the smartphone’s camera based on their quality and novelty. The smartphone’s app provides on-the-fly reconstruction feedback to users co-involved in the acquisitions. The server is composed of an incremental SfM algorithm that processes the received images by seamlessly merging them into a single sparse point cloud using bundle adjustment. Dense image matching algorithm can be lunched to derive denser point clouds. The reconstruction details, experiments and performance evaluation are presented and discussed.

scholarly journals Updating Geospatial Data by Creating a High Resolution Digital Surface Model

2018 ◽  
Vol 8 (2) ◽  
pp. 51-58 ◽  
Author(s):  
Iuliana Adriana Cuibac Picu
Keyword(s):  
Laser Scanning ◽  
Smart Cities ◽  
Geographic Information ◽  
Geospatial Data ◽  
Aerial Images ◽  
Aerial Photographs ◽  
Planning System ◽  
Surface Model ◽  
Digital Surface Model ◽  
Digital Terrain

Abstract Smart Cities are no longer just an aspiration, they are a necessity. For a city to be smart, accurate data collection or improvement the existing ones is needed, also an infrastructure that allows the integration of heterogeneous geographic information and sensor networks at a common technological point. Over the past two decades, laser scanning technology, also known as LiDAR (Light Detection and Ranging), has become a very important measurement method, providing high accuracy data and information on land topography, vegetation, buildings, and so on. Proving to be a great way to create Digital Terrain Models. The digital terrain model is a statistical representation of the terrain surface, including in its dataset the elements on its surface, such as construction or vegetation. The data use in the following article is from the LAKI II project “Services for producing a digital model of land by aerial scanning, aerial photographs and production of new maps and orthophotomaps for approximately 50 000 sqKm in 6 counties: Bihor, Arad, Hunedoara, Alba, Mures, Harghita including the High Risk Flood Zone (the border area with the Republic of Hungary in Arad and Bihor)”, which are obtained through LiDAR technology with a point density of 8 points per square meter. The purpose of this article is to update geospatial data with a higher resolution digital surface model and to demonstrate the differences between a digital surface models obtain by aerial images and one obtain by LiDAR technology. The digital surface model will be included in the existing geographic information system of the city Marghita in Bihor County, and it will be used to help develop studies on land use, transport planning system and geological applications. It could also be used to detect changes over time to archaeological sites, to create countur lines maps, flight simulation programs, or other viewing and modelling applications.

scholarly journals OBJECT BOUNDARIES REGULARIZATION USING THE DYNAMIC POLYLINE COMPRESSION ALGORITHM

2018 ◽  
Vol XLII-4 ◽  
pp. 541-546
Author(s):  
O. Saud Azeez ◽  
B. Kalantar ◽  
H. A. H. Al-Najjar ◽  
A. A. Halin ◽  
N. Ueda ◽  
...  
Keyword(s):  
3D Models ◽  
Compression Algorithm ◽  
Aerial Photographs ◽  
Average Error ◽  
Surface Model ◽  
Digital Surface Model ◽  
Spectral Difference ◽  
Image Objects ◽  
Image Layer ◽  
Quality Image

<p><strong>Abstract.</strong> This study presents a regularization approach to refine object boundaries for the purpose of buildings 3D modelling and reconstruction. Specifically, the derivative Normalized Digital Surface model (nDSM) image layer is firstly segmented using the classical multi-resolution segmentation followed by spectral difference segmentation. As the segmentation results can contain quite a number of boundary artefacts in the form geometrical distortions, the Dynamic Polyline Compression algorithm (DCPA) is applied as a regularization step in order to refine the outer boundaries, which removes the distortions. This results in higher quality image objects for the purpose of 3D models reconstruction. Experimental results after comparing between automatically extracted buildings and manually digitized aerial photographs indicate high completeness scores of 94%&amp;ndash;97% and correctness of 93%&amp;ndash;96%. Overall average error is minimized with very low Root Mean Square (RMS) and Overlay errors.</p>

Accuracy assessment using different UAV image overlaps

2019 ◽  
Vol 7 (3) ◽  
pp. 175-193
Author(s):  
Haval A. Sadeq
Keyword(s):  
Image Matching ◽  
Accuracy Assessment ◽  
3D Modelling ◽  
Surface Model ◽  
Digital Surface Model ◽  
Topographic Map ◽  
Aerial Vehicle ◽  
Close Range ◽  
Uav Image ◽  
Oblique Images

Unmanned aerial vehicle images are considered an important tool in close-range photogrammetry for topographic map production and 3D modelling using structure-from-motion approaches. The effect of overlap percentage in vertical and integrated vertical and oblique images on accuracy is evaluated. Analysis showed that the accuracy of the photogrammetric products (e.g., digital surface model and orthoimagery) is increased with the increased overlap percentage in vertical images. The accuracy is better when oblique images are integrated into vertical images than when only vertical images are used even with the same number of images. Furthermore, the building façade is constructed, but the building suffers from noise. Increasing the number of integrated vertical and oblique images improves the accuracy of the products and provides considerable precision to 3D modelling. This study showed that the improved result is due to the increased redundancy in image matching and optimised parameters of interior orientation through self-calibration. The images are processed using Pix4D software.

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