scholarly journals REGISTRATION OPTIMIZATION OF MOBILE HANDHELD SCANNER POINT CLOUDS WITH STATIC SCANS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 289-296
Author(s):  
V. Alteirac ◽  
H. Macher ◽  
T. Landes
Keyword(s):  
Point Clouds ◽  
Ease Of Use ◽  
Mobile Systems ◽  
Acquisition Time ◽  
Indoor Environments ◽  
Mobile System ◽  
Minimum Number ◽  
The One ◽  
Time Required ◽  
Handheld Scanner

Abstract. In recent years, 3D acquisition methods involving different types of scanners have undergone a phenomenal technological growth. Nowadays, mobile acquisition devices are popular because of their ease of use and their fairly competitive cost. Static scanners provide higher accuracy and more detail, but the acquisition time required with these systems is higher than with mobile systems. Mobile scanners are known for their high acquisition speed but lower point density and accuracy. Until now, the choice of the type of system to use was dependent on the geometry of the study area and the required accuracy. This research aims to find a way to optimize the survey by finding a compromise between the two types of devices, in order to take advantage of both systems for the same acquisition campaign. The first objective is to study the minimum number of static positions required for respecting the required accuracy. A solution is also proposed for compensating the drift of the mobile device. Secondly, the pertinence to use static stations for the principal loop and mobile system for adjoining rooms is investigated. The datasets chosen allow, on the one side, to quantify the limits of the mobile system for the acquisition of indoor buildings and, on the other side, to give recommendations regarding the configuration of static stations as a reference for mobile point clouds. Based on these experiments, a methodology is proposed for indoor environments to combine the use of the two acquisition systems and thus to save time in the field while still providing a good registration quality.

scholarly journals Semantic Mapping with Low-Density Point-Clouds for Service Robots in Indoor Environments

2020 ◽  
Vol 10 (20) ◽  
pp. 7154
Author(s):  
Carlos Medina Sánchez ◽  
Matteo Zella ◽  
Jesús Capitán ◽  
Pedro J. Marrón
Keyword(s):  
Deep Learning ◽  
Point Clouds ◽  
Physical Structure ◽  
Service Robots ◽  
Low Density ◽  
Indoor Environments ◽  
Density Point ◽  
Detection Of Objects ◽  
The One ◽  
Indoor Scenarios

The advancements in the robotic field have made it possible for service robots to increasingly become part of everyday indoor scenarios. Their ability to operate and reach defined goals depends on the perception and understanding of their surrounding environment. Detecting and positioning objects as well as people in an accurate semantic map are, therefore, essential tasks that a robot needs to carry out. In this work, we walk an alternative path to build semantic maps of indoor scenarios. Instead of relying on high-density sensory input, like the one provided by an RGB-D camera, and resource-intensive processing algorithms, like the ones based on deep learning, we investigate the use of low-density point-clouds provided by 3D LiDARs together with a set of practical segmentation methods for the detection of objects. By focusing on the physical structure of the objects of interest, it is possible to remove complex training phases and exploit sensors with lower resolution but wider Field of View (FoV). Our evaluation shows that our approach can achieve comparable (if not better) performance in object labeling and positioning with a significant decrease in processing time than established approaches based on deep learning methods. As a side-effect of using low-density point-clouds, we also better support people privacy as the lower resolution inherently prevents the use of techniques like face recognition.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

scholarly journals Deep Neural Networks Classification via Binary Error-Detecting Output Codes

2021 ◽  
Vol 11 (8) ◽  
pp. 3563
Author(s):  
Martin Klimo ◽  
Peter Lukáč ◽  
Peter Tarábek
Keyword(s):  
Neural Networks ◽  
Categorical Data ◽  
Coding Theory ◽  
Hamming Distance ◽  
Activation Function ◽  
Block Codes ◽  
Ease Of Use ◽  
Linear Block Codes ◽  
Binary Coding ◽  
The One

One-hot encoding is the prevalent method used in neural networks to represent multi-class categorical data. Its success stems from its ease of use and interpretability as a probability distribution when accompanied by a softmax activation function. However, one-hot encoding leads to very high dimensional vector representations when the categorical data’s cardinality is high. The Hamming distance in one-hot encoding is equal to two from the coding theory perspective, which does not allow detection or error-correcting capabilities. Binary coding provides more possibilities for encoding categorical data into the output codes, which mitigates the limitations of the one-hot encoding mentioned above. We propose a novel method based on Zadeh fuzzy logic to train binary output codes holistically. We study linear block codes for their possibility of separating class information from the checksum part of the codeword, showing their ability not only to detect recognition errors by calculating non-zero syndrome, but also to evaluate the truth-value of the decision. Experimental results show that the proposed approach achieves similar results as one-hot encoding with a softmax function in terms of accuracy, reliability, and out-of-distribution performance. It suggests a good foundation for future applications, mainly classification tasks with a high number of classes.

scholarly journals Simple low dose radiography allows precise lung volume assessment in mice

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Amara Khan ◽  
Andrea Markus ◽  
Thomas Rittmann ◽  
Jonas Albers ◽  
Frauke Alves ◽  
...  
Keyword(s):  
Lung Function ◽  
Whole Body ◽  
Acquisition Time ◽  
Micro Ct ◽  
Lung Volumes ◽  
X Ray ◽  
Promising Tool ◽  
Volume Assessment ◽  
Set Up ◽  
Time Required

AbstractX-ray based lung function (XLF) as a planar method uses dramatically less X-ray dose than computed tomography (CT) but so far lacked the ability to relate its parameters to pulmonary air volume. The purpose of this study was to calibrate the functional constituents of XLF that are biomedically decipherable and directly comparable to that of micro-CT and whole-body plethysmography (WBP). Here, we developed a unique set-up for simultaneous assessment of lung function and volume using XLF, micro-CT and WBP on healthy mice. Our results reveal a strong correlation of lung volumes obtained from radiographic XLF and micro-CT and demonstrate that XLF is superior to WBP in sensitivity and precision to assess lung volumes. Importantly, XLF measurement uses only a fraction of the radiation dose and acquisition time required for CT. Therefore, the redefined XLF approach is a promising tool for preclinical longitudinal studies with a substantial potential of clinical translation.

Research and Development of Clean-Energy Vehicles

2013 ◽  
Vol 345 ◽  
pp. 17-21
Author(s):  
Ting Jie Yang
Keyword(s):  
Research And Development ◽  
Electric Vehicle ◽  
Clean Energy ◽  
Mobile Systems ◽  
Energy Sources ◽  
Electric Motors ◽  
Mobile System ◽  
Electric Wheelchair ◽  
Electric Automobile ◽  
Institute Of Technology

This article presents the research and development of all electric vehicle (EV) in Department of HumanRobotics Saitama Institute of Technology, Japan .Electric mobile systems developed in our laboratory include a converted electric automobile,electric wheelchair and personal mobile robot.These mobile system s contribute to realize clean transportation since energy sources an d devices from all vehicles,i.e.,batteries and electric motors,does not deteriorate the environment.To drive motors for vehicle traveling,robotic technologies were applied.

scholarly journals Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors

Aerospace ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 94 ◽  
Author(s):  
Hriday Bavle ◽  
Jose Sanchez-Lopez ◽  
Paloma Puente ◽  
Alejandro Rodriguez-Ramos ◽  
Carlos Sampedro ◽  
...  
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Estimation Algorithm ◽  
Indoor Environments ◽  
3D Point Cloud ◽  
Flight Altitude ◽  
Cloud Data ◽  
3D Point Clouds ◽  
Laser Altimeters ◽  
Altitude Estimation

This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a flight altitude estimation algorithm, replacing the conventional sensors such as laser altimeters, barometers, or accelerometers, which have several limitations when used individually. Our proposed algorithm includes two stages: in the first stage, a fast clustering of the measured 3D point cloud data is performed, along with the segmentation of the clustered data into horizontal planes. In the second stage, these segmented horizontal planes are mapped based on the vertical distance with respect to the point cloud sensor frame of reference, in order to provide a robust flight altitude estimation even in presence of several static as well as dynamic ground obstacles. We validate our approach using the IROS 2011 Kinect dataset available in the literature, estimating the altitude of the RGB-D camera using the provided 3D point clouds. We further validate our approach using a point cloud sensor on board a UAV, by means of several autonomous real flights, closing its altitude control loop using the flight altitude estimated by our proposed method, in presence of several different static as well as dynamic ground obstacles. In addition, the implementation of our approach has been integrated in our open-source software framework for aerial robotics called Aerostack.

scholarly journals Estimating tree stem diameters and volume from smartphone photogrammetric point clouds

2019 ◽  
Vol 93 (3) ◽  
pp. 411-429 ◽  
Author(s):  
Maria Immacolata Marzulli ◽  
Pasi Raumonen ◽  
Roberto Greco ◽  
Manuela Persia ◽  
Patrizia Tartarino
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Stem Volume ◽  
Forest Plot ◽  
3D Point Clouds ◽  
Dense Point ◽  
Minimum Number ◽  
Scale Point

Abstract Methods for the three-dimensional (3D) reconstruction of forest trees have been suggested for data from active and passive sensors. Laser scanner technologies have become popular in the last few years, despite their high costs. Since the improvements in photogrammetric algorithms (e.g. structure from motion—SfM), photographs have become a new low-cost source of 3D point clouds. In this study, we use images captured by a smartphone camera to calculate dense point clouds of a forest plot using SfM. Eighteen point clouds were produced by changing the densification parameters (Image scale, Point density, Minimum number of matches) in order to investigate their influence on the quality of the point clouds produced. In order to estimate diameter at breast height (d.b.h.) and stem volumes, we developed an automatic method that extracts the stems from the point cloud and then models them with cylinders. The results show that Image scale is the most influential parameter in terms of identifying and extracting trees from the point clouds. The best performance with cylinder modelling from point clouds compared to field data had an RMSE of 1.9 cm and 0.094 m3, for d.b.h. and volume, respectively. Thus, for forest management and planning purposes, it is possible to use our photogrammetric and modelling methods to measure d.b.h., stem volume and possibly other forest inventory metrics, rapidly and without felling trees. The proposed methodology significantly reduces working time in the field, using ‘non-professional’ instruments and automating estimates of dendrometric parameters.

scholarly journals Statistical Analysis using traditional technique, Microsoft Excel and Predictive Analytic Software

10.17158/514 ◽  
2016 ◽  
Vol 19 (2) ◽  
Author(s):  
Jovelyn M. Durango ◽  
Carlito P. Yurango
Keyword(s):  
Statistical Analysis ◽  
Completion Time ◽  
Microsoft Excel ◽  
Instructional Tools ◽  
Traditional Technique ◽  
Significant Difference ◽  
Before And After ◽  
Computer Based ◽  
The One ◽  
Time Required

<p>The advent of technology has improved the way statistics is taught and learned. It is claimed that the use of computer-based instructional tools can actively explore the meaning of statistical concepts among the students, as well as enhance their learning experiences. This study aimed to compare three methods of statistical analysis namely, the traditional technique (use of the calculator), Microsoft Excel and Statistical Package for Social Sciences (SPSS) software. This investigation utilized the experimental design, specifically the One-Group Pretest – Posttest Design. There were six education students who self-assessed their attitude before and after the introduction of the use of various computation techniques and performed the statistical analysis considering also the completion time required for each process. Results of the study revealed an increase in the level of attitude among the respondents form the pretest to the posttest. Also, the cognitive level regardless of the approach was very high. However, the t-test failed to establish a significant difference in the attitude among the respondents. On the other hand, there were significant differences in both the test scores and completion time of the respondents in the three methods in favor of SPSS.</p><p> </p><p><strong>Keywords: </strong>Information technology, statistics, traditional technique, Microsoft excel, SPSS, comparative analysis, experimental research design, Davao City, Philippines. </p>

scholarly journals RECONSTRUCTION OF INDOOR MODELS USING POINT CLOUDS GENERATED FROM SINGLE-LENS REFLEX CAMERAS AND DEPTH IMAGES

2015 ◽  
Vol XL-4/W5 ◽  
pp. 99-102
Author(s):  
F. Tsai ◽  
T.-S. Wu ◽  
I.-C. Lee ◽  
H. Chang ◽  
A. Y. S. Su
Keyword(s):  
Data Processing ◽  
Data Acquisition ◽  
Three Dimensional ◽  
Point Clouds ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Indoor Environments ◽  
Single Lens ◽  
Processing Procedure ◽  
Data Processing Procedure

This paper presents a data acquisition system consisting of multiple RGB-D sensors and digital single-lens reflex (DSLR) cameras. A systematic data processing procedure for integrating these two kinds of devices to generate three-dimensional point clouds of indoor environments is also developed and described. In the developed system, DSLR cameras are used to bridge the Kinects and provide a more accurate ray intersection condition, which takes advantage of the higher resolution and image quality of the DSLR cameras. Structure from Motion (SFM) reconstruction is used to link and merge multiple Kinect point clouds and dense point clouds (from DSLR color images) to generate initial integrated point clouds. Then, bundle adjustment is used to resolve the exterior orientation (EO) of all images. Those exterior orientations are used as the initial values to combine these point clouds at each frame into the same coordinate system using Helmert (seven-parameter) transformation. Experimental results demonstrate that the design of the data acquisition system and the data processing procedure can generate dense and fully colored point clouds of indoor environments successfully even in featureless areas. The accuracy of the generated point clouds were evaluated by comparing the widths and heights of identified objects as well as coordinates of pre-set independent check points against in situ measurements. Based on the generated point clouds, complete and accurate three-dimensional models of indoor environments can be constructed effectively.

Teleworking in the Field of Financial Audit in the Context Generated by the COVID-19 Pandemic

2021 ◽  
Vol 19 (163) ◽  
pp. 501-515
Author(s):  
Nicoleta FARCANE ◽  
◽  
Ovidiu-Constantin Bunget ◽  
Rodica BLIDISEL ◽  
Alin-Constantin DUMITRESCU ◽  
...  
Keyword(s):  
Information Technologies ◽  
Virtual Space ◽  
Economic Context ◽  
Financial Audit ◽  
Travelling Time ◽  
Professional Practitioners ◽  
The One ◽  
Time Required ◽  
Restrictive Measures

In the sensitive socio-economic context generated by the COVID-19 pandemic, teleworking was, in many fields, a way to continue the activity while complying to the measures imposed by law in order to fight the spread of the new Coronavirus. On the one hand, teleworking offers flexibility in setting the work schedule, eliminates travelling time to and from the worksite and allows to attract competent employees from all over the world, by means of digitalisation. On the other hand, working from home is a challenge. The time required to transfer the activity in the virtual space, and the additional training necessary for the use of innovative information technologies can reduce efficiency and affect the work-life balance. This paper focuses on the audit profession, which had to rethink remote auditing so as to comply with the restrictive measures, but at the same time to avoid affecting the quality of audit missions. The questionnaire distributed among professional practitioners, members of the CFAR, helped us identify the perception of Romanian financial auditors on the variables influencing the efficiency of the audit work carried out in the “new normal” and the extent to which teleworking could become a practice in future financial audit missions.

Sign in / Sign up

Export Citation Format

Share Document