scholarly journals 3D Reconstruction of Non-Rigid Plants and Sensor Data Fusion for Agriculture Phenotyping

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4115
Author(s):  
Gustavo Scalabrini Sampaio ◽  
Leandro Augusto da Silva ◽  
Maurício Marengoni
Keyword(s):  
3D Models ◽  
Sensor Data ◽  
Novel Technique ◽  
Depth Images ◽  
Background Removal ◽  
Great Transformation ◽  
Processing Module ◽  
Corn Plants ◽  
Cycle Monitoring ◽  
First Time

Technology has been promoting a great transformation in farming. The introduction of robotics; the use of sensors in the field; and the advances in computer vision; allow new systems to be developed to assist processes, such as phenotyping, of crop’s life cycle monitoring. This work presents, which we believe to be the first time, a system capable of generating 3D models of non-rigid corn plants, which can be used as a tool in the phenotyping process. The system is composed by two modules: an terrestrial acquisition module and a processing module. The terrestrial acquisition module is composed by a robot, equipped with an RGB-D camera and three sets of temperature, humidity, and luminosity sensors, that collects data in the field. The processing module conducts the non-rigid 3D plants reconstruction and merges the sensor data into these models. The work presented here also shows a novel technique for background removal in depth images, as well as efficient techniques for processing these images and the sensor data. Experiments have shown that from the models generated and the data collected, plant structural measurements can be performed accurately and the plant’s environment can be mapped, allowing the plant’s health to be evaluated and providing greater crop efficiency.

scholarly journals RobotP: A Benchmark Dataset for 6D Object Pose Estimation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1299
Author(s):  
Honglin Yuan ◽  
Tim Hoogenkamp ◽  
Remco C. Veltkamp
Keyword(s):  
Pose Estimation ◽  
Ground Truth ◽  
3D Models ◽  
Depth Image ◽  
Great Success ◽  
Estimation Algorithms ◽  
Depth Images ◽  
Object Pose Estimation ◽  
Image Pairs ◽  
Bounding Boxes

Deep learning has achieved great success on robotic vision tasks. However, when compared with other vision-based tasks, it is difficult to collect a representative and sufficiently large training set for six-dimensional (6D) object pose estimation, due to the inherent difficulty of data collection. In this paper, we propose the RobotP dataset consisting of commonly used objects for benchmarking in 6D object pose estimation. To create the dataset, we apply a 3D reconstruction pipeline to produce high-quality depth images, ground truth poses, and 3D models for well-selected objects. Subsequently, based on the generated data, we produce object segmentation masks and two-dimensional (2D) bounding boxes automatically. To further enrich the data, we synthesize a large number of photo-realistic color-and-depth image pairs with ground truth 6D poses. Our dataset is freely distributed to research groups by the Shape Retrieval Challenge benchmark on 6D pose estimation. Based on our benchmark, different learning-based approaches are trained and tested by the unified dataset. The evaluation results indicate that there is considerable room for improvement in 6D object pose estimation, particularly for objects with dark colors, and photo-realistic images are helpful in increasing the performance of pose estimation algorithms.

scholarly journals UNDERWATER PHOTOGRAMMETRY DIGITAL SURFACE MODEL (DSM) OF THE SUBMERGED SITE OF THE ANCIENT LIGHTHOUSE NEAR QAITBAY FORT IN ALEXANDRIA, EGYPT

2019 ◽  
Vol XLII-2/W10 ◽  
pp. 1-8 ◽  
Author(s):  
M. Abdelaziz ◽  
M. Elsayed
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Data Gathering ◽  
Archaeological Site ◽  
3D Models ◽  
Surface Model ◽  
Digital Surface Model ◽  
Architectural Elements ◽  
3D Photogrammetry ◽  
First Time

<p><strong>Abstract.</strong> Underwater photogrammetry in archaeology in Egypt is a completely new experience applied for the first time on the submerged archaeological site of the lighthouse of Alexandria situated on the eastern extremity of the ancient island of Pharos at the foot of Qaitbay Fort at a depth of 2 to 9 metres. In 2009/2010, the CEAlex launched a 3D photogrammetry data-gathering programme for the virtual reassembly of broken artefacts. In 2013 and the beginning of 2014, with the support of the Honor Frost Foundation, methods were developed and refined to acquire manual photographic data of the entire underwater site of Qaitbay using a DSLR camera, simple and low cost materials to obtain a digital surface model (DSM) of the submerged site of the lighthouse, and also to create 3D models of the objects themselves, such as statues, bases of statues and architectural elements. In this paper we present the methodology used for underwater data acquisition, data processing and modelling in order to generate a DSM of the submerged site of Alexandria’s ancient lighthouse. Until 2016, only about 7200&amp;thinsp;m<sup>2</sup> of the submerged site, which exceeds more than 13000&amp;thinsp;m<sup>2</sup>, was covered. One of our main objectives in this project is to georeference the site since this would allow for a very precise 3D model and for correcting the orientation of the site as regards the real-world space.</p>

scholarly journals SYNTHETIC VISION SYSTEM CALIBRATION FOR CONFORM PROJECTION ON THE PILOT’S HEAD-UP DISPLAY

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 575-581
Author(s):  
S. Danilov ◽  
M. Kozyrev ◽  
M. Grechanichenko ◽  
L. Grodzitskiy ◽  
V. Mizginov ◽  
...  
Keyword(s):  
Situational Awareness ◽  
Vision System ◽  
Digital Terrain Model ◽  
3D Models ◽  
Sensor Data ◽  
Training Dataset ◽  
Learning Approaches ◽  
Terrain Model ◽  
Front Window ◽  
Calibration Algorithm

Abstract. Situational awareness of the crew is critical for the safety of the air flight. Head-up display allows providing all required flight information in front of the pilot over the cockpit view visible through the cockpit’s front window. This device has been created for solving the problem of informational overload during piloting of an aircraft. While computer graphics such as scales and digital terrain model can be easily presented on the such display, errors in the Head-up display alignment for correct presenting of sensor data pose challenges. The main problem arises from the parallax between the pilot’s eyes and the position of the camera. This paper is focused on the development of an online calibration algorithm for conform projection of the 3D terrain and runway models on the pilot’s head-up display. The aim of our algorithm is to align the objects visible through the cockpit glass with their projections on the Head-up display. To improve the projection accuracy, we use an additional optical sensor installed on the aircraft. We combine classical photogrammetric techniques with modern deep learning approaches. Specifically, we use an object detection neural network model to find the runway area and align runway projection with its actual location. Secondly, we re-project the sensor’s image onto the 3D model of the terrain to eliminate errors caused by the parallax. We developed an environment simulator to evaluate our algorithm. Using the simulator we prepared a large training dataset. The dataset includes 2000 images of video sequences representing aircraft’s motion during takeoff, landing and taxi. The results of the evaluation are encouraging and demonstrate both qualitatively and quantitatively that the proposed algorithm is capable of precise alignment of the 3D models projected on a Head-up display.

scholarly journals MULTI-SENSOR DATA ACQUISITION AND INTEGRATION PROCESSES FOR THE STUDY AND DOCUMENTATION OF THE CHURCH OF SANTA MARIA DEGLI ANGELI IN PIZZOFALCONE IN NAPLES

2021 ◽  
Vol XLVI-M-1-2021 ◽  
pp. 571-578
Author(s):  
M. Pulcrano ◽  
S. Scandurra ◽  
E. Fragalà ◽  
D. Palomba ◽  
A. di Luggo
Keyword(s):  
Comparative Analysis ◽  
Data Acquisition ◽  
Critical Analysis ◽  
3D Models ◽  
Sensor Data ◽  
Complete Representation ◽  
Passive Sensors ◽  
Santa Maria ◽  
The Church ◽  
3D Digital Models

Abstract. The paper presents the results of a research carried out on the Church of Santa Maria degli Angeli in Pizzofalcone in Naples, in which multi-sensor surveys have been performed in order to assess the architectonical, geometrical and colorimetric characteristics of the majestic basilica. The use of integrated technologies made it possible to realize 3D digital models that allowed the complete representation of the building, integrating data and filling the gaps of the different previous surveys. The performances of the various reality-based technologies employed have been subjected to critical analysis in order to maximize their potential, optimize survey and data elaboration phases, and obtain the expected results. These latter have been defined through the derived digital re-elaborations and representations. Hence, the objective of the research is to carry out a comparative analysis on the 3D models generated through the different active and passive sensors employed in order to proceed with their integration and achieve an accurate, original and updated methodology of building survey.

Formation of Sub-100 NM GE Wires on Si by E-Beam Evaporation/Lithography

1995 ◽  
Vol 380 ◽  
Author(s):  
C. Deng ◽  
J. C. Wu ◽  
C. J. Barbero ◽  
T. W. Sigmon ◽  
M. N. Wybourne
Keyword(s):  
Cross Section ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Si Substrates ◽  
Novel Technique ◽  
Atomic Force ◽  
Transmission Electron ◽  
First Time ◽  
Scanning Electron

ABSTRACTA fabrication process for sub-100 nm Ge wires on Si substrates is reported for the first time. Wires with a cross section of 6 × 57 nm2 are demonstrated. The wire structures are analyzed by atomic force (AFM), scanning electron (SEM), and transmission electron microscopy (TEM). Sample preparation for TEM is performed using a novel technique using both pre and in situ deposition of multiple protection layers using a Focused Ion Beam (FIB) micromachining system.

Traversability Analysis of a Novel One-DOF Robotic Leg

2013 ◽  
Author(s):  
Lionel Birglen ◽  
Carlos Ruella
Keyword(s):  
Degrees Of Freedom ◽  
Mobile Robotics ◽  
Simulation Algorithm ◽  
Novel Technique ◽  
The Past ◽  
Robotic Leg ◽  
Leg Design ◽  
First Time

In legged mobile robotics the most common approach is to design fully actuated legs with several degrees of freedom (DOF) in order to successfully navigate through rough terrains. However, simpler leg architectures with as few as one-DOF have been developed in the past to achieve the very same goal. The ability of these simpler legs to traverse uneven terrains is arguably limited with respect to multi-DOF designs, but in some applications the reduction of the DOF and hence, of the number of actuators, as well as the simplicity of the associated control could be a great advantage and the decisive argument. In this paper, the authors propose a novel one-DOF robotic leg that has been specially designed to achieve the greatest robustness possible with respect to the difficult terrains it has to traverse. In order to do that, a method to analyze and optimize any one-DOF robotic leg with respect to its ability to overcome obstacles is proposed here. This method is based on a simple and efficient novel technique to generate synthetic terrains combined with a simulation algorithm estimating the traversability of the particular one-DOF leg design under scrutiny. To illustrate the generality of the proposed method, it is used to design both an optimal leg with the architecture presented here for the first time and also, one with the most common one-DOF leg architecture found in the literature.

scholarly journals Fingal's Cave

2018 ◽  
Vol 7 (14) ◽  
pp. 5
Author(s):  
Shona Kirsty Noble
Keyword(s):  
3D Models ◽  
Practical Implementation ◽  
Immersive Virtual Reality ◽  
Complete Understanding ◽  
Acoustic Characteristics ◽  
Cultural Narrative ◽  
Heritage Sites ◽  
Heritage Site ◽  
The Impact ◽  
First Time

Fingal’s Cave: an Audiovisual Experience is an immersive virtual reality application that combines 3D models, a narrative soundscape and interactive auralisation in a recreation of a visit to Fingal’s Cave. This research explores the importance of audio in heritage visualisations and its practical implementation. Fingal’s Cave is a sea cave on the Isle of Staffa off the west coast of Scotland revered for its extraordinary acoustics. Audio is extremely important in the history and culture of Fingal’s Cave and it has long been romanticised, inspiring countless folklore, art, poetry and music. The visualisation is designed to encourage viewers to become a part of the cultural narrative and explore the cave for themselves, move around and speak to hear their voice auralised as it would be inside the cave. This is the first time the acoustic characteristics of a heritage site have been included in a visualisation in this interactive manner. This paper reviews whether auralisation is effective and meaningful and supports a creative response to heritage sites. The impact of the visualisation in terms of engaging with communities of interest and in the field of audio in heritage visualisation is discussed. The research suggests it is necessary that audio be included in heritage visualisations to give a full and complete understanding of how people experience it.

scholarly journals Calibration and accuracy analysis of a focused plenoptic camera

2014 ◽  
Vol II-3 ◽  
pp. 205-212 ◽  
Author(s):  
N. Zeller ◽  
F. Quint ◽  
U. Stilla
Keyword(s):  
Curve Fitting ◽  
Depth Map ◽  
Reference Points ◽  
New Methods ◽  
Model Based ◽  
Depth Images ◽  
Fitting Method ◽  
Plenoptic Camera ◽  
Curve Fitting Method ◽  
First Time

In this article we introduce new methods for the calibration of depth images from focused plenoptic cameras and validate the results. We start with a brief description of the concept of a focused plenoptic camera and how from the recorded raw image a depth map can be estimated. For this camera, an analytical expression of the depth accuracy is derived for the first time. In the main part of the paper, methods to calibrate a focused plenoptic camera are developed and evaluated. The optical imaging process is calibrated by using a method which is already known from the calibration of traditional cameras. For the calibration of the depth map two new model based methods, which make use of the projection concept of the camera are developed. These new methods are compared to a common curve fitting approach, which is based on Taylor-series-approximation. Both model based methods show significant advantages compared to the curve fitting method. They need less reference points for calibration than the curve fitting method and moreover, supply a function which is valid in excess of the range of calibration. In addition the depth map accuracy of the plenoptic camera was experimentally investigated for different focal lengths of the main lens and is compared to the analytical evaluation.

scholarly journals POSSIBILITIES OF SPATIAL CORRELATION OF 3D MODELS IN AN ARCHAEOLOGICAL AUGMENTED REALITY APPLICATION

2021 ◽  
Vol XLVI-M-1-2021 ◽  
pp. 355-359
Author(s):  
D. Kaimaris ◽  
T. Roustanis ◽  
K. Klimantakis ◽  
I. A. Karolos ◽  
P. Patias
Keyword(s):  
Augmented Reality ◽  
Mobile Devices ◽  
3D Models ◽  
Archaeological Sites ◽  
Detection And Tracking ◽  
Augmented Reality Application ◽  
Building Walls ◽  
First Time ◽  
Made In

Abstract. The use of Augmented Reality (AR) technology is widespread in countless archaeological sites and a variety of applications. Archaeological excavations lead to archaeological finds, some of which are transported for preservation and then for exhibition in museums (jewelry, vases, etc.), while another part of them is documented in detail and remains in situ (eg building walls), roads, grave covers, etc.). However, after the registration of the archaeological finds, it is impossible to observe them. As part of our research project, we will develop for the first time AR methodology and procedures for the observation of covered archaeological finds on mobile devices (smart phones, tablets), which were registered after their documentation. AR technology in recent years has seen great growth in terms of implementation platforms and available software, as well as the tools developed to support it. These tools either make their appearance in the form of frameworks, extending the capabilities of an existing engine, or function as independent services. At the same time, progress has been made in the field of sensors of mobile devices, which makes the compatibility of hardware and software another issue to be researched. As part of the development of the above application for mobile devices, an evaluation is made of the most widespread AR Frameworks that support the Unity3d Game Engine and the compatibility / interoperability with the sensors of different categories of mobile devices. The frameworks were checked and evaluated for placement and tracking of the positions of the 3D covered objects. In this paper also, methodologies and techniques used in space detection and tracking are presented and evaluated.

Robust Signal Recovery From Distorted Nonlinear Sensor Data

2003 ◽  
Author(s):  
Sugathevan Suranthiran ◽  
Suhada Jayasuriya
Keyword(s):  
Model Uncertainty ◽  
Signal Reconstruction ◽  
Sensor Data ◽  
Signal Recovery ◽  
Chirp Signal ◽  
Accurate Model ◽  
Design And Implementation ◽  
Novel Technique ◽  
Model Based ◽  
Nonlinear Sensors

In an attempt to facilitate the design and implementation of memory-less nonlinear sensors, the signal reconstruction schemes are analyzed and necessary modifications are proposed to improve the accuracy and minimize errors in sensor measurements. The problem of recovering chirp signal from the distorted nonlinear output is considered and an efficient reconstruction approach is developed. Model uncertainty is a serious issue with any model-based algorithms and a novel technique, which uses a norminal model instead of an accurate model and produces the results that are robust to model uncertainty, is proposed.

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