Search Results (49)

The evolution of photogrammetry has been significantly influenced by advancements in camera technology, particularly the emergence of spherical cameras. These devices offer extensive photographic coverage and are increasingly utilised in many photogrammetry applications due to their significant user-friendly configuration, especially in their low-cost versions. Despite their advantages, these cameras are subject to high image distortion. This necessitates specialised calibration solutions related to fisheye images, which represent the primary geometry of the raw files. This paper evaluates fisheye calibration processes for the effective utilisation of low-cost spherical cameras, for the purpose of 3D reconstruction and the verification of geometric stability. Calibration optical parameters include focal length, pixel positions, and distortion coefficients. Emphasis was placed on the evaluation of solutions for camera calibration, calibration network design, and the assessment of software or toolboxes that support the correspondent geometry and calibration for processing. The efficiency in accuracy, correctness, computational time, and stability parameters was assessed with the influence of calibration parameters based on the accuracy of the 3D reconstruction. The assessment was conducted using a previous case study of graffiti on an underpass in Wiesbaden, Germany. The robust calibration solution is a two-step calibration process, including a pre-calibration stage and the consideration of the best possible network design. Fisheye undistortion was performed using OpenCV, and finally, calibration parameters were optimized with self-calibration through bundle adjustment to achieve both calibration parameters and 3D reconstruction using Agisoft Metashape software. In comparison to 3D calibration, self-calibration, and a pre-calibration strategy, the two-step calibration process has demonstrated an average improvement of 2826 points in the 3D sparse point cloud and a 0.22 m decrease in the re-projection error value derived from the front lens images of two individual spherical cameras. The accuracy and correctness of the 3D point cloud and the statistical analysis of parameters in the two-step calibration solution are presented as a result of the quality assessment of this paper and in comparison with the 3D point cloud produced by a laser scanner. Full article

The diameter at breast height (DBH) is a fundamental index used to characterize trees and establish forest inventories. The conventional method of measuring the DBH involves using steel tape meters, rope, and calipers. Alternatively, this study has shown that it can be calculated automatically using image-based algorithms, thus reducing time and effort while remaining cost-effective. The method consists of three main steps: image acquisition using a fisheye lens, 3D point cloud generation using structure-from-motion (SfM)-based image processing, and improved DBH estimation. The results indicate that this proposed methodology is comparable to traditional urban forest DBH measurements, with a root-mean-square error ranging from 0.7 to 2.4 cm. The proposed approach has been evaluated using real-world data, and it has been determined that the F-score assessment metric achieves a maximum of 0.91 in a university garden comprising 74 trees. The successful automated DBH measurements through SfM combined with fisheye lenses demonstrate the potential to improve urban tree inventories. Full article

Thermal comfort studies are paramount in enhancing future urban living conditions, and hemispherical photography has emerged as a widely employed field measurement technique in outdoor thermal comfort research. This comprehensive review systematically analyzed 142 outdoor thermal comfort studies conducted over the past decade using hemispherical photography methods, revealing that its primary application lies in objectively describing environmental information and constructing associated indices. In contrast, the number of studies focusing on subjectively assessing environmental factors remains relatively low; however, it is rapidly increasing due to its demonstrated effectiveness and convenience compared to other methodologies within this domain. Overall, despite certain limitations, such as higher labor costs and limited temporal/spatial coverage when describing environmental information, hemispherical photography still retains its advantage of providing accurate data acquisition for outdoor thermal comfort research. In recent years, advancements in mobile measurement tools and techniques have enhanced the richness and versatility of acquired information while leveraging the image specificity inherent to hemispherical photography, which continues to play a pivotal role in subjective assessments related to human perception of outdoor thermal comfort. Full article

Growing light pollution is increasingly studied in terrestrial environments. However, research on night lights in coastal ecosystems is limited. We aimed to complement spaceborne remote sensing with ground-based hemispheric photos to quantify the exposure of coastal habitats to light pollution. We used a calibrated DSLR Canon camera with a fisheye lens to photograph the night sky in 24 sites in the rapidly developing area of Moreton Bay, Queensland, Australia, extracting multiple brightness metrics. We then examined the use of the LANcubeV2 photometer and night-time satellite data from SDGSAT-1 for coastal areas. We found that the skies were darker in less urbanized areas and on islands compared with the mainland. Sky brightness near the zenith was correlated with satellite observations only at a coarse spatial scale. When examining light pollution horizontally above the horizon (60–80° degrees below the zenith), we found that the seaward direction was brighter than the landward direction in most sites due to urban glow on the seaward side. These findings emphasize the importance of ground measurements of light pollution alongside satellite imagery. In order to reduce the exposure of coastal ecosystems to light pollution, actions need to go beyond sites with conservation importance and extend to adjacent urban areas. Full article

We present a sensor that utilizes a modified single-frequency split beam metasurface reflector to measure the refractive index of materials ranging from one to three. Samples are placed into a cavity between a PCB-etched dielectric and a reflecting ground plane. It is illuminated using a 10.525 GHz free-space transmit horn with reflecting angles measured by sweeping a receiving horn around the setup. Predetermined changes in measured angles determined through simulations will coincide with the material’s index. The sensor is designed using the Fourier transform method of array synthesis and verified with FEM simulations. The device is fabricated using PCB milling and 3D printing. The quality of the sensor is verified by characterizing 3D printed dielectric samples of various infill percentages and thicknesses. Without changing the metasurface design, the sensing performance is extended to accommodate larger sample thicknesses by including a modified 3D printed fish-eye lens mounted in front of the beam splitter; this helps to exaggerate changes in reflected angles for those samples. All the methods presented are in agreement and verified with single-frequency index measurements using Snell’s law. This device may offer a viable alternative to traditional index characterization methods, which often require large sample sizes for single-frequency measurements or expensive equipment for multi-frequency parameter extraction. Full article

The leaf area index (LAI) is an essential indicator for assessing vegetation growth and understanding the dynamics of forest ecosystems and is defined as the ratio of the total leaf surface area in the plant canopy to the corresponding surface area below it. LAI has applications for obtaining information on plant health, carbon cycling, and forest ecosystems. Due to their price and portability, mobile devices are becoming an alternative to measuring LAI. In this research, a new method for estimating LAI using a smart device with a fisheye lens (SFL) is proposed. The traditional Otsu method was enhanced to improve the accuracy and efficiency of foreground segmentation. The experimental samples were located in Gansu Ziwuling National Forest Park in Qingyang. In the accuracy parameter improvement experiment, the variance of the average LAI value obtained by using both zenith angle segmentation and azimuth angle segmentation methods was reduced by 50%. The results show that the segmentation of the front and back scenes of the new Otsu method is more accurate, and the obtained LAI values are more reliable. In the efficiency parameter improvement experiment, the time spent is reduced by 17.85% when the enhanced Otsu method is used to ensure that the data anomaly rate does not exceed 10%, which improves the integration of the algorithm into mobile devices and the efficiency of obtaining LAI. This study provides a fast and effective method for the near-ground measurement of forest vegetation productivity and provides help for the calculation of forest carbon sequestration efficiency, oxygen release rate, and forest water and soil conservation ability. Full article

This study introduces a groundbreaking antenna system, the directive Metasurface Half-Maxwell Fish-Eye (MHMF) lens antenna, tailored specifically for Internet-of-Things (IoT) networks. Designed to operate at 60 GHz, this antenna ingeniously integrates a dipole antenna within a parallel-plate waveguide to illuminate a Half-Maxwell Fish-Eye (HMFE) lens. The HMFE lens serves as a focal point, enabling a crucial high gain for IoT operations. The integration of metasurface structures facilitates the attainment of the gradient refractive index essential for the lens surface. By employing commercial Ansys HFSS software, extensive numerical simulations were conducted to meticulously refine the design, focusing particularly on optimizing the dimensions of unit cells, notably the modified H-shaped cells within the parallel waveguides housing the beam launchers. A functional prototype of the antenna was constructed using a standard PCB manufacturing process. Rigorous testing in an anechoic chamber confirmed the functionality of these manufactured devices, with the experimental results closely aligning with the simulated findings. Far-field measurements have further confirmed the effectiveness of the antenna, establishing it as a high-gain antenna solution suitable for IoT applications. Specifically, it operates effectively within the 60 GHz range of the electromagnetic spectrum, which is crucial for ensuring reliable communication in IoT devices. The directive HMFE lens antenna represents a significant advancement in enhancing IoT connectivity and capabilities. Leveraging innovative design concepts and metasurface technology, it heralds a new era of adaptable and efficient IoT systems. Full article

The leaf area index (LAI) is one of the core parameters reflecting the growth status of vegetation. The continuous long-term observation of the LAI is key when assessing the dynamic changes in the energy exchange of ecosystems and the vegetation’s response indicators to climate change. The errors brought about by non-standard operations in manual LAI measurements hinder the further research utilization of this parameter. The long-term automatic LAI observation network is helpful in reducing errors from manual measurements. To further test the applicability of automatic LAI observation instruments in forest environments, this study carried out comparative validation research of the LAI-NOS (LAI automatic network observation system) at the Wanglang Mountain Ecological Remote Sensing Comprehensive Observation Station, China, comparing it with the results measured by the LAI-2200 Plant Canopy Analyzer (LI-COR, Lincoln, NE, USA), the LAI-probe handheld instrument, and a fisheye lens digital camera (DHP method). Instead of using the original “smoothest window” method, a new method, the “sunrise–sunset” method, is used to extract daily LAI-NOS LAI, and the corresponding confidence level is used to filter the data. The results of the data analysis indicate the following: LAI-NOS has a high data stability. The automatically acquired daily data between two consecutive days has a small deviation and significant correlations. Single-angle/multi-angle LAI measurement results of the LAI-NOS have good correlations with the LAI-2200 (R² = 0.512/R² = 0.652), the LAI-probe (R² = 0.692/R² = 0.619), and the DHP method (R² = 0.501/R² = 0.394). The daily LAI obtained from the improved method, when compared to the original method, both show the same vegetation growth trend. However, the improved method has a smaller dispersion. This study confirms the stability and accuracy of automatic observation instruments in mountainous forests, demonstrating the distinct advantages of automatic measurement instruments in the long-term ground observation of LAIs. Full article

To achieve a lightweight design and wide field of view for the automatic alignment system in wireless optical communication, in the receiving antenna—a fisheye lens is incorporated as the receiving optical system. This feature enables the detection and tracking of lasers. The system utilizes a micro motor as the control servo system and a four-quadrant detector as the detection unit. Sequential and non-sequential ray tracing techniques were used to simulate the analysis of the fish-eye lens. Point array diagrams, ray trace diagrams, and encircled energy analysis were utilized to evaluate the spot’s quality. The simulation results demonstrate that the fish-eye lens has a field of view of 120°, and the spot with 80% energy has a diameter smaller than 30 μm. The experimental results indicate that the fish-eye lens effectively captures the light beam within the range of ±30°. The simulated and experimental results for the sum and difference frequency amplitudes show good agreement. The outdoor experiments have demonstrated a tracking error of 22.757 μrad in this system. After alignment, the average output optical power of the detector is 3.23 μW, and the detected waveform amplitude is 12.48 mV. These findings demonstrate the system’s potential for automatic alignment in wireless optical communication. Additionally, the system is relatively simple and practical. Full article

This study shows the results of the analysis of the photogrammetric use of 360-degree cameras in complex heritage-related scenes. The goal is to take advantage of the large field of view provided by these sensors and reduce the number of images used to cover the entire scene compared to those needed using conventional cameras. We also try to minimize problems derived from camera geometry and lens characteristics. In this regard, we used a multi-sensor camera composed of six fisheye lenses, applying photogrammetric procedures to several funerary structures. The methodology includes the analysis of several types of spherical images obtained using different stitching techniques and the comparison of the results of image orientation processes considering these images and the original fisheye images. Subsequently, we analyze the possible use of the fisheye images to model complex scenes by reducing the use of ground control points, thus minimizing the need to apply surveying techniques to determine their coordinates. In this regard, we applied distance constraints based on a previous extrinsic calibration of the camera, obtaining results similar to those obtained using a traditional schema based on points. The results have allowed us to determine the advantages and disadvantages of each type of image and configuration, providing several recommendations regarding their use in complex scenes. Full article

The aspheric surface is a commonly used method to improve the imaging quality of the fisheye lens, but it is difficult to determine the position and initial value. Based on the wave aberration theory of the plane-symmetric optical system, a method of using an aspheric surface to design a fisheye lens is proposed, which can quickly determine the appropriate aspheric surface to improve the imaging performance. First, the wave aberration of each optical surface of the fisheye lens is calculated and its aberration characteristics are analyzed. Then, a numerical evaluation function is reported based on the aberration distribution of the fisheye lens on the image plane. According to the functional relationship between the evaluation function and the aspheric coefficient, the position of the aspheric surface and the initial value of the aspheric coefficient can be calculated. Finally, the adaptive and normalized real-coded genetic algorithm is used as the evaluation function to optimize the fisheye lens using an aspheric surface. The proposed method can provide an effective solution for designing a fisheye lens using an aspheric surface. Full article

Leaf area index is a key structural parameter for biological and physical processes. Korea is planning to launch CAS500-4 in 2025, so in situ data is needed to validate the leaf area index. Unlike other networks (e.g., NEON and TERN), establishing an elementary sampling unit is difficult in Korea due to the complex forest structure and rugged terrain. Therefore, pixel-level correspondence between the satellite product and fisheye footprints is the best way to verify in complex terrain. In this study, we analyzed the spatial footprint of fisheye lenses in different forest types using terrestrial LiDAR data for the first time. The three-dimensional forest structure was analyzed at various viewing zenith angles, and the footprint radius was approximately 3 m at view zenith angle (VZA) 20° and approximately 10 m at VZA 90°. We also analyzed the Z-values from terrestrial laser data and the plant area index on leafless seasons to assess the impact of obstacles, such as tree trunks, under various viewing zenith angles. The analysis showed that the influence of woody components increases dramatically as the VZA exceeds 40°. Such factors influenced the increase in LAI and the decrease in the clumping index as the VZA increased. Overall, we concluded that narrowing VZA between 20° and 40° is appropriate for Korean forests with complex structures. Full article

Continuous, robust, and precise localization is pivotal in enabling the autonomous operation of robots and aircraft in intricate environments, particularly in the absence of GNSS (global navigation satellite system) signals. However, commonly employed approaches, such as visual odometry and inertial navigation systems, encounter hindrances in achieving effective navigation and positioning due to issues of error accumulation. Additionally, the challenge of managing extensive map creation and exploration arises when deploying these systems on unmanned aerial vehicle terminals. This study introduces an innovative system capable of conducting long-range and multi-map visual SLAM (simultaneous localization and mapping) using monocular cameras equipped with pinhole and fisheye lens models. We formulate a graph optimization model integrating GNSS data and graphical information through multi-sensor fusion navigation and positioning technology. We propose partitioning SLAM maps based on map health status to augment accuracy and resilience in large-scale map generation. We introduce a multi-map matching and fusion algorithm leveraging geographical positioning and visual data to address excessive discrete mapping, leading to resource wastage and reduced map-switching efficiency. Furthermore, a multi-map-based visual SLAM online localization algorithm is presented, adeptly managing and coordinating distinct geographical maps in different temporal and spatial domains. We employ a quadcopter to establish a testing system and generate an aerial image dataset spanning several kilometers. Our experiments exhibit the framework’s noteworthy robustness and accuracy in long-distance navigation. For instance, our GNSS-assisted multi-map SLAM achieves an average accuracy of 1.5 m within a 20 km range during unmanned aerial vehicle flights. Full article

This study presents a visual-only odometry technique of a low-profile pallet robot using image feature tracking in ground plane images generated from a fisheye camera. The fisheye camera is commonly used in many robot vision applications because it provides a larger field of view (FoV) around a robot. However, because of the large radial distortion, the fisheye image is generally converted to a pinhole image for visual feature tracking or matching. Although the radial distortion can be eliminated via image undistortion with the lens calibration parameters, it causes several side effects, such as degraded image resolution and a significant reduction in the FoV. In this paper, instead of using the pinhole model, we propose to generate a ground plane image (GPI) from the fisheye image. GPI is a virtual top-view image that only contains the ground plane at the front of the robot. First, the original fisheye image is projected to several virtual pinhole images to generate a cubemap. Second, the front and bottom faces of the cubemap are projected to a GPI. Third, the GPI is homographically transformed again to further reduce image distortion. As a result, an accurate ortho-rectified ground plane image is obtained from the virtual top-view camera. For visual odometry using the ortho-rectified GPI, a number of 2D motion vectors are obtained using feature extraction and tracking between the previous and current frames in the GPI. By calculating a scaled motion vector, which is the measurement of the virtual wheel encoder of the mobile robot, we estimate the velocity and steering angle of the virtual wheel using the motion vector. Finally, we estimate the pose of the mobile robot by applying a kinematic model to the mobile robot. Full article

With the continuous progress of urbanization, contemporary scholars are increasingly focusing their attention on the study of urban microclimates. This research aims to investigate the relationship between urban morphology and microclimates in regions characterized by hot summers and cold winters. Environmental meteorological data, including temperature, solar radiation, and wind speed during the spring and summer seasons, were collected through on-site monitoring in a specific area of Shanghai. Various methods, such as on-site surveys and drone photography, were employed to obtain and analyze a range of urban morphological parameters, including floor area ratio (FAR) and greenery ratio (GnPR). The sky view factor (SVF) was determined using a fisheye lens technique. Subsequently, the collected datasets were analyzed to assess the varying impact of distinct urban morphological factors on microclimates. The findings indicate a significant correlation between different building morphology factors and temperature and solar radiation during spring, while their associations with wind speed become more prominent in summer. Notably, greenery and pavement demonstrate stronger correlations with temperature and radiation in summer, aligning with the seasonal growth patterns of plants. These research findings provide both a theoretical foundation and practical guidelines for the urban design of environmental microclimates. Full article