Article
Chemistry, Analytical
Adam Dlesk, Karel Vach, Karel Pavelka
Summary: The photogrammetric processing of thermal infrared images poses challenges due to low resolution and contrast. This can be overcome through co-processing of TIR and RGB images. Two solutions are presented in the article, each requiring different types of transformations which are discussed in terms of requirements, advantages, disadvantages, and accuracy in experiments.
Article
Environmental Sciences
Wei Huang, San Jiang, Wanshou Jiang
Summary: The study presents a new self-calibration method that only requires one GCP, categorizes camera distortion models into physical and mathematical models, combines strategies for optimizing camera parameters and fusing GNSS observations, and demonstrates through experimental results that it significantly alleviates the bowl effect in weakly structured long corridor UAV images.
Article
Engineering, Electrical & Electronic
Okay Arik, Seniha Esen Yuksel
Summary: A novel camera calibration method is proposed in this work, using photos of buildings and acceleration vectors to replace external calibrators. Despite not needing external objects, this method shows competitive accuracy compared to popular calibrator-based methods.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Optics
Ashraf A. A. Beshr, Hossam El-Din Fawzy, Ehab A. A. Eldin, Jong Wan Hu, Fathi A. Abdelmgeed
Summary: This paper introduces the application of digital measuring techniques, specifically Digital Close Range Photogrammetry (DCRP), in the detection of deformation in post-tensioned structural elements (PTSEs). The use of digital equipment and a terrestrial laser scanner (TLS) allows for highly accurate monitoring of PTSE camber, with deviations not exceeding 0.01 mm.
OPTICS AND LASER TECHNOLOGY
(2024)
Article
Chemistry, Analytical
Kuan-Ying Lin, Yi-Hsing Tseng, Kai-Wei Chiang
Summary: The precision modelling of intrinsic camera geometry is a common issue in the fields of photogrammetry and computer vision. This paper clarifies the definitions of intrinsic camera parameters used in each field and proposes an algorithm to transform these parameters. The proposed transformation method is more rigorous than conventional methods and enables users to apply mixed software in the fields of photogrammetry and computer vision.
Article
Agronomy
Nobuo Kochi, Atsushi Hayashi, Yota Shinohara, Takanari Tanabata, Kunihiro Kodama, Sachiko Isobe
Summary: In this study, an all-around 3D plant modeling system was developed using images and is capable of measuring plants non-destructively without any contact. The system utilizes a method of 3D reconstruction from multiple images and enables 3D modeling by simply capturing images with a camera. The image-based method offers flexibility as it can use commercially available products and accommodate different plant shapes and sizes.
Article
Chemistry, Analytical
Photis Patonis
Summary: This paper develops and implements a procedure for calibrating image sensors and evaluating results in mobile devices. Two methods, an OpenCV function and a photogrammetry method using the same camera model, are used for calibration. A method using single-image rectification is proposed for evaluating the calibration results. A standard is proposed for the number and shooting angles of photographs used in the calibration. The procedure and software application are tested in a case study.
Article
Environmental Sciences
Frank Liebold, David Mader, Hannes Sardemann, Anette Eltner, Hans-Gerd Maas
Summary: Newly developed low-cost cameras exhibit lens distortion patterns that cannot be well handled with existing models. This study presents an approach that divides the image sensor and distortion modeling into two zones for the application of an extended radial lens distortion model. Practical tests show that the new model reduces the distortion better than the standard model.
Article
Engineering, Mechanical
Roberto Del Sal, Loris Dal Bo, Emanuele Turco, Andrea Fusiello, Alessandro Zanarini, Roberto Rinaldo, Paolo Gardonio
Summary: This study presents a simulation and experimental investigation on measuring the flexural deflection shape of a beam using multiple synchronous cameras. The results show that the accuracy of the measurements significantly improves with an increasing number of cameras and large opening angles between the cameras.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Computer Science, Information Systems
Jae-Yeul Kim, Jong-Eun Ha
Summary: The extrinsic calibration of a 2D camera and a 2D LiDAR is necessary to integrate information from both sensors in the same coordinate system. Various geometric constraints, such as point-plane, point-line, and point-point constraints, are used for the extrinsic calibration. This study proposes a new algorithm for automatic extrinsic calibration using point-line correspondences. Experimental results demonstrate the feasibility of the proposed algorithm, showing a 15.3% improvement compared to the linear solution after nonlinear minimization.
Article
Chemistry, Analytical
Aleksandra Jasinska, Krystian Pyka, Elzbieta Pastucha, Henrik Skov Midtiby
Summary: Recently, the term smartphone photogrammetry gained popularity. The research aimed to determine the suitability of using the SfM-MVS method with self-calibration in smartphone photogrammetry. The study involved testing the geometric stability of smartphone cameras and developing 3D models using images from selected smartphones. The results showed that introducing calibration values obtained in a test field improved the geometry of the 3D models compared to self-calibration.
Article
Remote Sensing
Julio Manuel de Luis-Ruiz, Javier Sedano-Cibrian, Ruben Perez-Alvarez, Raul Pereda-Garcia, Beatriz Malagon-Picon
Summary: Monitoring energy efficiency and maintenance of buildings, infrastructure, and industrial facilities is common nowadays and has become more advanced with the use of UAV-mounted sensors for detecting issues in large facilities. This research proposes a methodology for generating and comparing thermal models with good precision, particularly in mining-industrial facilities where thermal conditions are crucial. The average differences and standard deviations between true measurements and those obtained from RGB and thermal models are provided, showing that while the RGB model is more accurate, the thermal model is adequate for achieving the set objectives.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Environmental Sciences
Hang Trieu, Per Bergstrom, Mikael Sjodahl, J. Gunnar Hellstrom, Patrik Andreasson, Henrik Lycksam
Summary: This study presents a multi-camera photogrammetric approach to measure the 3D velocity of free surface flow, which was validated through laboratory and natural river measurements, showing reliable estimation with sufficient accuracy.
Review
Geography, Physical
Rongjun Qin, Armin Gruen
Summary: The process of modern photogrammetry involves converting images and LiDAR data into usable products with the help of engineering-grade hardware and software components. While some data processing steps are automated, manual involvement is still required for reliable results. The recent development of machine learning techniques has attracted attention for its potential in addressing complex tasks in photogrammetry and computer vision.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2021)
Article
Engineering, Mechanical
P. Gardonio, G. Guernieri, E. Turco, L. Dal Bo, R. Rinaldo, A. Fusiello
Summary: This paper presents a new approach to reconstruct the sound radiation field produced by the flexural vibration of a distributed structure using video image acquisitions. The study focuses on tonal flexural vibration and sound radiation at specific resonance frequencies. The vibration and radiation fields are estimated using triangulation from images acquired with six cameras, and compared with measurements from a laser vibrometer and an array of microphones.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Environmental Sciences
Leonardo Josoe Biffi, Edson Mitishita, Veraldo Liesenberg, Anderson Aparecido dos Santos, Diogo Nunes Goncalves, Nayara Vasconcelos Estrabis, Jonathan de Andrade Silva, Lucas Prado Osco, Ana Paula Marques Ramos, Jorge Antonio Silva Centeno, Marcos Benedito Schimalski, Leo Rufato, Silvio Luis Rafaeli Neto, Jose Marcato Junior, Wesley Nunes Goncalves
Summary: In recent years, agriculture-related problems have been evaluated using artificial intelligence techniques and remote sensing systems. This paper presents an approach based on the ATSS deep learning method for efficient apple fruit detection, supporting apple production forecasting. The proposed method slightly outperformed other deep learning methods and was robust against most image corruptions.
Article
Forestry
Ana Karina Vieira da Silva, Marcus Vinicius Vieira Borges, Tays Silva Batista, Carlos Antonio da Silva Junior, Danielle Elis Garcia Furuya, Lucas Prado Osco, Larissa Pereira Ribeiro Teodoro, Fabio Henrique Rojo Baio, Ana Paula Marques Ramos, Wesley Nunes Goncalves, Jose Marcato Junior, Paulo Eduardo Teodoro, Hemerson Pistori
Summary: Machine learning techniques, combined with spectral vegetation indices from UAV imagery, show promise in predicting the diameter at breast height (DBH) and total height (Ht) of eucalyptus trees. Among various ML algorithms evaluated, random forest (RF) had overall superior estimation, while radial basis function (RBF) showed higher performance in predicting DBH in some cases. Support vector machine (SVM) obtained the smallest MAE in a specific test for predicting Ht.
Article
Environmental Sciences
Rorai Pereira Martins-Neto, Antonio Maria Garcia Tommaselli, Nilton Nobuhiro Imai, Hassan Camil David, Milto Miltiadou, Eija Honkavaara
Summary: This study investigated the estimation of stand and diversity variables in disturbed tropical forests using LiDAR data and machine learning techniques. By testing different transformations of LiDAR metrics and various machine learning methods, the study identified the best approach for estimating forest variables accurately in heterogeneous forests.
Article
Geochemistry & Geophysics
Renato Cesar dos Santos, Guilherme Gomes Pessoa, Andre Caceres Carrilho, Mauricio Galo
Summary: This letter proposes a new approach that combines five estimation strategies to improve the robustness of boundary extraction from airborne LiDAR data.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Leandro Higa, Jose Marcato Junior, Thiago Rodrigues, Pedro Zamboni, Rodrigo Silva, Laisa Almeida, Veraldo Liesenberg, Fabio Roque, Renata Libonati, Wesley Nunes Goncalves, Jonathan Silva
Summary: Fire in the Brazilian Pantanal poses a serious threat to biodiversity. Remote sensing research and the use of convolutional neural networks (CNN) can help detect active fires with higher precision. A proposed object detection method based on post-processing strategies shows promising results in accurately mapping active fire in the Pantanal.
Article
Chemistry, Analytical
Luiz Santos, Jose Marcato Junior, Pedro Zamboni, Mateus Santos, Liana Jank, Edilene Campos, Edson Takashi Matsubara
Summary: In this study, we assessed the performance of Convolutional Neural Network (CNN)-based approaches using mobile phone images to estimate regrowth density in tropical forages. The best regression model showed a mean absolute error of 7.70 and a correlation of 0.89, suggesting that deep learning on mobile phone images can successfully be used to estimate regrowth density in forages.
Article
Agronomy
Raquel Alves Oliveira, Jose Marcato Junior, Celso Soares Costa, Roope Nasi, Niko Koivumaki, Oiva Niemelainen, Jere Kaivosoja, Laura Nyholm, Hemerson Pistori, Eija Honkavaara
Summary: In this study, low-cost RGB images captured by a UAV were used along with convolutional neural networks to estimate dry matter yield and nitrogen concentration of grass swards. The results demonstrate that this approach is a promising and effective tool for practical applications.
Article
Chemistry, Analytical
Renato Cesar dos Santos, Ayman F. Habib, Mauricio Galo
Summary: The article proposes a weighted iterative changeable degree spline (WICDS) method for accurate contour modeling of building boundaries with occlusions. Experimental results demonstrate the effectiveness of the WICDS approach with simulated and real data.
Article
Forestry
Rorai Pereira Martins-Neto, Antonio Maria Garcia Tommaselli, Nilton Nobuhiro Imai, Eija Honkavaara, Milto Miltiadou, Erika Akemi Saito Moriya, Hassan Camil David
Summary: This study explores the use of different combinations of UAV hyperspectral data and LiDAR metrics to classify tree species in a degraded Brazilian Atlantic Forest remnant. By combining spectral data with geometric information from LiDAR, the classification accuracy was improved in a complex tropical forest.
Article
Agronomy
Erika Akemi Saito Moriya, Nilton Nobuhiro Imai, Antonio Maria Garcia Tommaselli, Eija Honkavaara, David Luciano Rosalen
Summary: This study used vegetation indices and hyperspectral remote sensing technology to successfully detect the areas affected by sugarcane mosaic disease, providing an effective tool for crop disease monitoring.
Editorial Material
Agronomy
Antonio Maria Garcia Tommaselli
Proceedings Paper
Geography, Physical
R. C. dos Santos, M. Galo, A. F. Habib
Summary: This paper proposes a building detection method based on clustering and eigenvalues, which can automatically detect buildings without the need for training and provides optimal neighborhood definition for local attribute estimation. Additionally, a refinement step is introduced to minimize classification errors.
XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION II
(2022)
Proceedings Paper
Geography, Physical
L. R. Porto, N. N. Imai, A. M. G. Tommaselli, L. Salvador Neto
Summary: This study analysed the radiometric calibration technique proposed by Agrowing for processing data from a multispectral camera. The results showed that the calibration procedure can significantly improve the reflectance factor of the images, especially in the red-edge band.
XXIV ISPRS CONGRESS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION I
(2022)
Proceedings Paper
Geography, Physical
L. F. Castanheiro, A. M. G. Tommaselli, M. Machado, G. H. Santos, I. S. Norberto, T. T. Reis
Summary: This paper presents an assessment of a wide-angle laser scanner and a SLAM algorithm for estimating trajectory and generating a 3D map of the environment. The study used a backpack platform with an OS0-128 Ouster laser scanner to acquire laser data in an area with urban and forest features. The Web SLAM algorithm was used to estimate the trajectory and generate a 3D map, which was then transformed into the ground coordinate system. Three datasets were used for analysis, and the results showed centimetric accuracy.
XXIV ISPRS CONGRESS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION I
(2022)
Article
Environmental Sciences
Adilson Berveglieri, Nilton N. Imai, Luiz E. Christovam, Maria L. B. T. Galo, Antonio M. G. Tommaselli, Eija Honkavaara
Summary: The research explores the relationship between forest vertical structure variability and the NDVI temporal trajectory associated with vegetation vigor in a tropical forest in Brazil. By analyzing NDVI trajectory clusters, it was found that 59.9% were related to preserved areas, 30.1% to transitional areas, and 10.0% to degraded areas, allowing for the understanding of spectral development in heterogeneous forests with different succession stages.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2021)