scholarly journals ONLY IMAGE BASED FOR THE 3D METRIC SURVEY OF GOTHIC STRUCTURES BY USING FRAME CAMERAS AND PANORAMIC CAMERAS

2016 ◽  
Vol XLI-B5 ◽  
pp. 363-370
Author(s):  
A. Pérez Ramos ◽  
G. Robleda Prieto
Keyword(s):  
Laser Scanning ◽  
Imaging Techniques ◽  
Laser Scanner ◽  
Point Clouds ◽  
Office Work ◽  
Light Conditions ◽  
External Quality ◽  
Panoramic Cameras ◽  
Dense Point ◽  
Close Range

Indoor Gothic apse provides a complex environment for virtualization using imaging techniques due to its light conditions and architecture. Light entering throw large windows in combination with the apse shape makes difficult to find proper conditions to photo capture for reconstruction purposes. Thus, documentation techniques based on images are usually replaced by scanning techniques inside churches. Nevertheless, the need to use Terrestrial Laser Scanning (TLS) for indoor virtualization means a significant increase in the final surveying cost. So, in most cases, scanning techniques are used to generate dense point clouds. However, many Terrestrial Laser Scanner (TLS) internal cameras are not able to provide colour images or cannot reach the image quality that can be obtained using an external camera. Therefore, external quality images are often used to build high resolution textures of these models. This paper aims to solve the problem posted by virtualizing indoor Gothic churches, making that task more affordable using exclusively techniques base on images. It reviews a previous proposed methodology using a DSRL camera with 18-135 lens commonly used for close range photogrammetry and add another one using a HDR 360° camera with four lenses that makes the task easier and faster in comparison with the previous one. Fieldwork and office-work are simplified. The proposed methodology provides photographs in such a good conditions for building point clouds and textured meshes. Furthermore, the same imaging resources can be used to generate more deliverables without extra time consuming in the field, for instance, immersive virtual tours. In order to verify the usefulness of the method, it has been decided to apply it to the apse since it is considered one of the most complex elements of Gothic churches and it could be extended to the whole building.

scholarly journals ONLY IMAGE BASED FOR THE 3D METRIC SURVEY OF GOTHIC STRUCTURES BY USING FRAME CAMERAS AND PANORAMIC CAMERAS

2016 ◽  
Vol XLI-B5 ◽  
pp. 363-370 ◽  
Author(s):  
A. Pérez Ramos ◽  
G. Robleda Prieto
Keyword(s):  
Laser Scanning ◽  
Imaging Techniques ◽  
Laser Scanner ◽  
Point Clouds ◽  
Office Work ◽  
Light Conditions ◽  
External Quality ◽  
Panoramic Cameras ◽  
Dense Point ◽  
Close Range

Indoor Gothic apse provides a complex environment for virtualization using imaging techniques due to its light conditions and architecture. Light entering throw large windows in combination with the apse shape makes difficult to find proper conditions to photo capture for reconstruction purposes. Thus, documentation techniques based on images are usually replaced by scanning techniques inside churches. Nevertheless, the need to use Terrestrial Laser Scanning (TLS) for indoor virtualization means a significant increase in the final surveying cost. So, in most cases, scanning techniques are used to generate dense point clouds. However, many Terrestrial Laser Scanner (TLS) internal cameras are not able to provide colour images or cannot reach the image quality that can be obtained using an external camera. Therefore, external quality images are often used to build high resolution textures of these models. This paper aims to solve the problem posted by virtualizing indoor Gothic churches, making that task more affordable using exclusively techniques base on images. It reviews a previous proposed methodology using a DSRL camera with 18-135 lens commonly used for close range photogrammetry and add another one using a HDR 360° camera with four lenses that makes the task easier and faster in comparison with the previous one. Fieldwork and office-work are simplified. The proposed methodology provides photographs in such a good conditions for building point clouds and textured meshes. Furthermore, the same imaging resources can be used to generate more deliverables without extra time consuming in the field, for instance, immersive virtual tours. In order to verify the usefulness of the method, it has been decided to apply it to the apse since it is considered one of the most complex elements of Gothic churches and it could be extended to the whole building.

scholarly journals PEDESTRIAN DETECTION BY LASER SCANNING AND DEPTH IMAGERY

2016 ◽  
Vol XLI-B3 ◽  
pp. 465-468
Author(s):  
A. Barsi ◽  
T. Lovas ◽  
B. Molnar ◽  
A. Somogyi ◽  
Z. Igazvolgyi
Keyword(s):  
Laser Scanning ◽  
Pedestrian Detection ◽  
Laser Scanner ◽  
Point Clouds ◽  
Shopping Mall ◽  
Complex Flow ◽  
Video Footage ◽  
Flow Parameters ◽  
Dense Point ◽  
Commercial Applications

Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements without disturbing and changing their motion. Profile laser scanner and depth camera have been applied to capture the geometry of the moving people as time series. Procedures have been developed to derive complex flow parameters, such as count, volume, walking direction and velocity from laser scanned point clouds. Since no images are captured from the faces of pedestrians, no privacy issues raised. The paper includes accuracy analysis of the estimated parameters based on video footage as reference. Due to the dense point clouds, detailed geometry analysis has been conducted to obtain the height and shoulder width of pedestrians and to detect whether luggage has been carried or not. The derived parameters support safety (e.g. detecting critical pedestrian density in mass events), security (e.g. detecting prohibited baggage in endangered areas) and commercial applications (e.g. counting pedestrians at all entrances/exits of a shopping mall).

scholarly journals CLOSE RANGE UAV ACCURATE RECORDING AND MODELING OF ST-PIERRE-LE-JEUNE NEO-ROMANESQUE CHURCH IN STRASBOURG (FRANCE)

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 519-526 ◽  
Author(s):  
A. Murtiyoso ◽  
P. Grussenmeyer ◽  
T. Freville
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Geographical Information ◽  
Close Range Photogrammetry ◽  
Dense Matching ◽  
Dense Point ◽  
Close Range ◽  
Calibration Accuracy ◽  
3D Documentation

Close-range photogrammetry is an image-based technique which has often been used for the 3D documentation of heritage objects. Recently, advances in the field of image processing and UAVs (Unmanned Aerial Vehicles) have resulted in a renewed interest in this technique. However, commercially ready-to-use UAVs are often equipped with smaller sensors in order to minimize payload and the quality of the documentation is still an issue. In this research, two commercial UAVs (the Sensefly Albris and DJI Phantom 3 Professional) were setup to record the 19<sup>th</sup> century St-Pierre-le-Jeune church in Strasbourg, France. Several software solutions (commercial and open source) were used to compare both UAVs’ images in terms of calibration, accuracy of external orientation, as well as dense matching. Results show some instability in regards to the calibration of Phantom 3, while the Albris had issues regarding its aerotriangulation results. Despite these shortcomings, both UAVs succeeded in producing dense point clouds of up to a few centimeters in accuracy, which is largely sufficient for the purposes of a city 3D GIS (Geographical Information System). The acquisition of close range images using UAVs also provides greater LoD flexibility in processing. These advantages over other methods such as the TLS (Terrestrial Laser Scanning) or terrestrial close range photogrammetry can be exploited in order for these techniques to complement each other.

scholarly journals Visibility analysis of point cloud in close range photogrammetry

2014 ◽  
Vol II-5 ◽  
pp. 9-16 ◽  
Author(s):  
B. Alsadik ◽  
M. Gerke ◽  
G. Vosselman
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Visibility Analysis ◽  
Close Range Photogrammetry ◽  
Visible Points ◽  
Dense Point ◽  
Close Range ◽  
Mathematical Techniques

The ongoing development of advanced techniques in photogrammetry, computer vision (CV), robotics and laser scanning to efficiently acquire three dimensional geometric data offer new possibilities for many applications. The output of these techniques in the digital form is often a sparse or dense point cloud describing the 3D shape of an object. Viewing these point clouds in a computerized digital environment holds a difficulty in displaying the visible points of the object from a given viewpoint rather than the hidden points. This visibility problem is a major computer graphics topic and has been solved previously by using different mathematical techniques. However, to our knowledge, there is no study of presenting the different visibility analysis methods of point clouds from a photogrammetric viewpoint. The visibility approaches, which are surface based or voxel based, and the hidden point removal (HPR) will be presented. Three different problems in close range photogrammetry are presented: camera network design, guidance with synthetic images and the gap detection in a point cloud. The latter one introduces also a new concept of gap classification. Every problem utilizes a different visibility technique to show the valuable effect of visibility analysis on the final solution.

scholarly journals Strategy for Determining the Stochastic Distance Characteristics of the 2D Laser Scanner Z + F Profiler 9012A with Special Focus on the Close Range

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2253 ◽  
Author(s):  
Erik Heinz ◽  
Markus Mettenleiter ◽  
Heiner Kuhlmann ◽  
Christoph Holst
Keyword(s):  
Stochastic Models ◽  
Laser Scanning ◽  
Laser Light ◽  
Laser Scanner ◽  
Point Clouds ◽  
Mobile Systems ◽  
Special Focus ◽  
Distance Measurements ◽  
3D Point Clouds ◽  
Close Range

Kinematic laser scanning with moving platforms has been used for the acquisition of 3D point clouds of our environment for many years. A main application of these mobile systems is the acquisition of the infrastructure, e.g., the road surface and buildings. Regarding this, the distance between laser scanner and object is often notably shorter than 20 m. In the close range, however, divergent incident laser light can lead to a deterioration of the precision of laser scanner distance measurements. In the light of this, we analyze the distance precision of the 2D laser scanner Z + F Profiler 9012A, purpose-built for kinematic applications, in the range of up to 20 m. In accordance with previous studies, a clear dependency between scan rate, intensity of the backscattered laser light and distance precision is evident, which is used to derive intensity-based stochastic models for the sensor. For this purpose, a new approach for 2D laser scanners is proposed that is based on the static scanning of surfaces with different backscatter. The approach is beneficial because the 2D laser scanner is operated in its normal measurement mode, no sophisticated equipment is required and no model assumptions for the scanned surface are made. The analysis reveals a lower precision in the range below 5 m caused by a decreased intensity. However, the Z + F Profiler 9012A is equipped with a special hardware-based close range optimization partially compensating for this. Our investigations show that this optimization works best at a distance of about 2 m. Although increased noise remains a critical factor in the close range, the derived stochastic models are also valid below 5 m.

scholarly journals PEDESTRIAN DETECTION BY LASER SCANNING AND DEPTH IMAGERY

2016 ◽  
Vol XLI-B3 ◽  
pp. 465-468
Author(s):  
A. Barsi ◽  
T. Lovas ◽  
B. Molnar ◽  
A. Somogyi ◽  
Z. Igazvolgyi
Keyword(s):  
Laser Scanning ◽  
Pedestrian Detection ◽  
Laser Scanner ◽  
Point Clouds ◽  
Shopping Mall ◽  
Complex Flow ◽  
Video Footage ◽  
Flow Parameters ◽  
Dense Point ◽  
Commercial Applications

Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements without disturbing and changing their motion. Profile laser scanner and depth camera have been applied to capture the geometry of the moving people as time series. Procedures have been developed to derive complex flow parameters, such as count, volume, walking direction and velocity from laser scanned point clouds. Since no images are captured from the faces of pedestrians, no privacy issues raised. The paper includes accuracy analysis of the estimated parameters based on video footage as reference. Due to the dense point clouds, detailed geometry analysis has been conducted to obtain the height and shoulder width of pedestrians and to detect whether luggage has been carried or not. The derived parameters support safety (e.g. detecting critical pedestrian density in mass events), security (e.g. detecting prohibited baggage in endangered areas) and commercial applications (e.g. counting pedestrians at all entrances/exits of a shopping mall).

scholarly journals Towards footwear manufacturing 4.0: shoe sole robotic grasping in assembling operations

2021 ◽  
Author(s):  
Guillermo Oliver ◽  
Pablo Gil ◽  
Jose F. Gomez ◽  
Fernando Torres
Keyword(s):  
Industry 4.0 ◽  
Laser Scanner ◽  
Point Clouds ◽  
Average Score ◽  
Low Density ◽  
Contour Extraction ◽  
Shoe Industry ◽  
Simulated Environment ◽  
Dense Point ◽  
Different Shapes

AbstractIn this paper, we present a robotic workcell for task automation in footwear manufacturing such as sole digitization, glue dispensing, and sole manipulation from different places within the factory plant. We aim to make progress towards shoe industry 4.0. To achieve it, we have implemented a novel sole grasping method, compatible with soles of different shapes, sizes, and materials, by exploiting the particular characteristics of these objects. Our proposal is able to work well with low density point clouds from a single RGBD camera and also with dense point clouds obtained from a laser scanner digitizer. The method computes antipodal grasping points from visual data in both cases and it does not require a previous recognition of sole. It relies on sole contour extraction using concave hulls and measuring the curvature on contour areas. Our method was tested both in a simulated environment and in real conditions of manufacturing at INESCOP facilities, processing 20 soles with different sizes and characteristics. Grasps were performed in two different configurations, obtaining an average score of 97.5% of successful real grasps for soles without heel made with materials of low or medium flexibility. In both cases, the grasping method was tested without carrying out tactile control throughout the task.

Optical methods and wireless sensors for monitoring of bridges

2019 ◽  
Author(s):  
Cosmin Popescu ◽  
Björn Täljsten ◽  
Thomas Blanksvärd ◽  
Gabriel Sas ◽  
Alexander Jimenez ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Crack Opening ◽  
Point Clouds ◽  
Base Station ◽  
Optical Methods ◽  
Railway Bridges ◽  
Wireless Monitoring ◽  
Building Information ◽  
Close Range ◽  
Traffic Disturbance

<p>Six railway bridges have been scanned using infrared scanning (IR), close range photogrammetry (CRP) and terrestrial laser scanning (TRS) to reconstruct point clouds and evaluate the potential of the technologies for building information modelling (BIM) and assessment purposes. The results may also help to improve bridge inspection routines. This is done by evaluating the accuracy and quality of the point clouds, time consumption, safety and traffic disturbance.</p><p>Wireless Monitoring has been used in a demonstration project in Sweden. It consists of a base station and nodes. The base station receives signals from the node antennas and transmits the signals to the cloud. The nodes are equipped with strain gauges, crack opening devices, temperature sensors or other suitable sensors for the investigation purpose. Results from the methods and conclusions regarding further use will be presented.</p>

Application of close range photogrammetry in structural health monitoring by processing generated point cloud datasets

2021 ◽  
Author(s):  
Ali Mirzazade ◽  
Cosmin Popescu ◽  
Thomas Blanksvärd ◽  
Björn Täljsten
Keyword(s):  
Health Monitoring ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Optical Data ◽  
Small Scale ◽  
Relevant Parameter ◽  
Bridge Inspection ◽  
Close Range Photogrammetry ◽  
Close Range

<p>In bridge inspection, vertical displacement is a relevant parameter for both short and long-term health monitoring. Assessing change in deflections could also simplify the assessment work for inspectors. Recent developments in digital camera technology and photogrammetry software enables point cloud with colour information (RGB values) to be generated. Thus, close range photogrammetry offers the potential of monitoring big and small-scale damages by point clouds. The current paper aims to monitor geometrical deviations in Pahtajokk Bridge, Northern Sweden, using an optical data acquisition technique. The bridge in this study is scanned two times by almost one year a part. After point cloud generation the datasets were compared to detect geometrical deviations. First scanning was carried out by both close range photogrammetry (CRP) and terrestrial laser scanning (TLS), while second scanning was performed by CRP only. Analyzing the results has shown the potential of CRP in bridge inspection.</p>

scholarly journals Segmentation and Multi-Scale Convolutional Neural Network-Based Classification of Airborne Laser Scanner Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3347 ◽  
Author(s):  
Zhishuang Yang ◽  
Bo Tan ◽  
Huikun Pei ◽  
Wanshou Jiang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Region Growing ◽  
Point Clouds ◽  
Classification Method ◽  
Multi Scale ◽  
Airborne Laser

The classification of point clouds is a basic task in airborne laser scanning (ALS) point cloud processing. It is quite a challenge when facing complex observed scenes and irregular point distributions. In order to reduce the computational burden of the point-based classification method and improve the classification accuracy, we present a segmentation and multi-scale convolutional neural network-based classification method. Firstly, a three-step region-growing segmentation method was proposed to reduce both under-segmentation and over-segmentation. Then, a feature image generation method was used to transform the 3D neighborhood features of a point into a 2D image. Finally, feature images were treated as the input of a multi-scale convolutional neural network for training and testing tasks. In order to obtain performance comparisons with existing approaches, we evaluated our framework using the International Society for Photogrammetry and Remote Sensing Working Groups II/4 (ISPRS WG II/4) 3D labeling benchmark tests. The experiment result, which achieved 84.9% overall accuracy and 69.2% of average F1 scores, has a satisfactory performance over all participating approaches analyzed.

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