Camera Placement Research Articles

Neural Observation Field Guided Hybrid Optimization of Camera Placement

Neural Observation Field Guided Hybrid Optimization of Camera Placement

Machine learning solutions for adaptive traffic signal control: A review of image-based approaches

This paper gives an overview and performance evaluation of various machine learning models implemented in management of urban traffic congestions, more specifically, adaptive traffic signal control systems. It considers a review of deep learning algorithms including R- CNN, Fast R-CNN, Faster R-CNN, SSD, YOLO v4, and YOLOv8, with regard to their efficiencies for vehicle detection and traffic prediction under varying scenarios. Certain traffic conditions, camera placements, and environmental factors—related performance for each of the models are discussed. The major performance in most of the scenarios was depicted by the YOLO v4. However, at the same time, YOLOv8 has shown potential to do much better than YOLO v4 on image processing and the resultant accuracy. It also proposes a new algorithm for traffic light timing, whose efficacy is tested using the SUMO simulation platform. While results have shown improvements in urban traffic management, a review underlines that such is in deep need of extensive real-world testing. Future directions should include views from varied angles and weather conditions, and the detection of emergency vehicles, probably with specialized datasets.

Influence of Camera Placement on UGV Teleoperation Efficiency in Complex Terrain

Many fields, where human health and life are at risk, are increasingly utilizing mobile robots and UGVs (Unmanned Ground Vehicles). They typically operate in teleoperation mode (control based on the projected image, outside the operator’s direct field of view), as autonomy is not yet sufficiently developed and key decisions should be made by the man. Fast and effective decision making requires a high level of situational and action awareness. It relies primarily on visualizing the robot’s surroundings and end effectors using cameras and displays. This study aims to compare the effectiveness of three solutions of robot area imaging systems using the simultaneous transmission of images from three cameras while driving a UGV in complex terrain.

Design of a diamond-based in-vessel soft x-ray detector for the SPARC tokamak.

The in-vessel silicon diode arrays that are used for soft x-ray detection in many tokamaks are sensitive to neutron damage, making them unsuitable for burning plasma devices such as SPARC. In such a device, the silicon diodes would need to be placed far from the plasma-limiting their field of view-or an alternative detector could be used. Here, we present the design of a camera containing an array of chemical vapor deposition single-crystal diamonds, which will be placed in the upper and lower port plugs of the SPARC tokamak with a large enough view of the poloidal cross section to enable tomographic inversion. The camera design presented here is optimized to provide a wide field of view of the poloidal cross section. Simulated plasma conditions are used to estimate the x-ray signal that this detector array will receive and to fine-tune the camera placement within the tokamak.

Developing novel non-assistant help operation in dual-portal robotic-assisted thoracic surgery (neoDRATS)

ObjectiveTo introduce and evaluate the non-assistant help operation in dual-portal robotic-assisted thoracic surgery (neoDRATS), a novel technique designed to eliminate the need for skilled assistants by using all 4 robotic arms independently during anatomical lung surgery. MethodsPatients were placed in the lateral decubitus position under general anesthesia with single-lung ventilation. The da Vinci Xi Surgical System was used, with specific configurations for right- and left-side operations. The neoDRATS technique used a 4-cm working port and a 1.8-cm secondary port, with detailed guidelines for optimal setup and robotic arm manipulation. ResultsThe neoDRATS approach demonstrated successful surgical outcomes without the need for a skilled assistant. The use of a 0° camera and careful placement of instruments minimized interference within the thoracic cavity. The technique provided smooth operability and minimized postoperative discomfort. Video demonstrations of right and left upper lobectomies are provided to illustrate the approach. ConclusionsNeoDRATS offers a practical, safe, and minimally invasive alternative to conventional multiportal and uniportal robotic-assisted thoracic surgeries. This technique simplifies the surgical process, particularly in settings with limited availability of skilled assistants, and represents a significant advancement in robotic thoracic surgery. Further refinement and clinical integration of neoDRATS are anticipated as robotic innovations continue to evolve.

Leveraging BIM for Enhanced Camera Allocation Planning at Construction Job Sites: A Voxel-Based Site Coverage and Overlapping Analysis

In the construction industry, the imperative for visual surveillance mechanisms is underscored by the need for safety monitoring, resources, and progress tracking, especially with the adoption of vision intelligence technology. Traditional camera installation plans often move toward coverage and cost objectives without considering substantial coverage overlap, inflating processing and storage requirements, and complicating subsequent analyses. To address these issues, this research proposes a voxel-based site coverage and overlapping analysis for camera allocation planning in parametric BIM environments, called the PBA approach. The first step is to collect information from the BIM model, which is the input for the parametric modeling step. After that, the PBA approach simulates the virtual devices and the construction layout by employing visual language programming and then generates a coverage area. Lastly, the performance simulation and evaluation of various placement scenarios against predefined criteria are conducted, including visual coverage and overlapping optimization for eliminating data redundancy purposes. The proposed approach is evaluated through its application to construction projects. The results from these various implementations indicate a marked decrease in data overlap and an overall enhancement in surveillance efficacy. This research contributes a novel, BIM-centric solution to visual information adoption in the construction industry, offering a scalable approach to optimize camera placement while mitigating overlapping areas.

Neurological Examination via Telemedicine: An Updated Review Focusing on Movement Disorders.

Patients with movement disorders such as Parkinson's disease (PD) living in remote and underserved areas often have limited access to specialized healthcare, while the feasibility and reliability of the video-based examination remains unclear. The aim of this narrative review is to examine which parts of remote neurological assessment are feasible and reliable in movement disorders. Clinical studies have demonstrated that most parts of the video-based neurological examination are feasible, even in the absence of a third party, including stance and gait-if an assistive device is not required-bradykinesia, tremor, dystonia, some ocular mobility parts, coordination, and gross muscle power and sensation assessment. Technical issues (video quality, internet connection, camera placement) might affect bradykinesia and tremor evaluation, especially in mild cases, possibly due to their rhythmic nature. Rigidity, postural instability and deep tendon reflexes cannot be remotely performed unless a trained healthcare professional is present. A modified version of incomplete Unified Parkinson's Disease Rating Scale (UPDRS)-III and a related equation lacking rigidity and pull testing items can reliably predict total UPDRS-III. UPDRS-II, -IV, Timed "Up and Go", and non-motor and quality of life scales can be administered remotely, while the remote Movement Disorder Society (MDS)-UPDRS-III requires further investigation. In conclusion, most parts of neurological examination can be performed virtually in PD, except for rigidity and postural instability, while technical issues might affect the assessment of mild bradykinesia and tremor. The combined use of wearable devices may at least partially compensate for these challenges in the future.

4D BIM and Reality Model–Driven Camera Placement Optimization for Construction Monitoring

4D BIM and Reality Model–Driven Camera Placement Optimization for Construction Monitoring

Clustered and rotating designs as a strategy to obtain precise detection rates in camera trapping studies

Abstract Camera traps have transformed the way we monitor wildlife and are now routinely used to address questions from a wide range of ecological and conservation aspects. Sampling design optimization and a better understanding of drivers determining the precision of detection rates (i.e. the number of detections per unit of effort) are important methodological issues. Little attention has been focused on the effect of placing more than one camera on each sampling point (hereafter, clustered design), and/or rotating (i.e. redeploying) the cameras to new placements during the sampling period. We explored the differences in the precision of detection rates between clustered vs. single camera designs when cameras remained in the same location during the study. Furthermore, the effect of keeping the placement of cameras fixed or rotating them (i.e. moving them to new locations during the sampling period), when a limited number of camera devices are available, was also evaluated. We used simulations and field data to test differences in detection rate precision for the different sampling designs. We simulated three different population distributions (random, trail‐based and aggregated) and three abundance scenarios. The simulations were validated with a field experiment focused on eight species with different behavioural traits, including artiodactyls, carnivores, lagomorphs, and birds. When a fixed number of sampling points were monitored simultaneously, clustered designs generally resulted in an increase in the precision of detection rates compared to single designs. The absolute reduction in the coefficient of variation by clustered designs was on average 0.07 units (min: 0.01, max: 0.15), which represents an average relative reduction in CV of 31% (min:6%, max:44%). An improvement in precision was also observed as a higher number of sampling points was used for all population distributions and sampling designs tested. When a fixed number of cameras were available, rotating the cameras to independent locations improved precision (an absolute reduction of 0.19 CV units) when monitoring aggregated populations, but not for random and trail‐based population distributions. Synthesis and applications: Our research provides a guideline for wildlife managers and researchers to improve the precision of camera trap detection rates and optimize resource allocation. In general, the study design should accommodate the behaviour of the target species (e.g. spatial aggregation and abundance), monitoring program logistic resources (both human and economic) and study area characteristics (e.g. accessibility and vandalism).

Expert elicitation of remote meat inspection prerequisites in Sweden using best-worst scaling (case 1)

Remote work technologies offer unprecedented flexibility to modernise official meat inspection (MI). Remote meat inspections, alongside on-site controls have a potential to make MI more sustainable when it comes to working conditions, logistic control hurdles and travel-related emissions. Nevertheless, preferences of meat control staff for features and technological set up of remote MI remain unknown.The paper investigates preferences of official Swedish MI staff for different features of remote MI. The study utilises a quantitative method, namely best-worst scaling to compare the relative importance of six aspects of remote inspections: camera location and settings, connectivity, availability of personnel at abattoirs, communication and language, security and fraud prevention, and ability to relay olfaction and haptics. The survey, administered in September–October 2023 was answered by 54.7% of the Swedish meat control staff employed by the Swedish Food Agency. The results show that respondents rate security and fraud prevention (Security) as the most important aspect for remote MI followed by connectivity and camera placement (Camera). Communication and language (Communication) and ability to relay olfaction and haptics (Senses) are considered the least important aspects. The latter findings can be explained by the fact that Official Veterinarians, which represent the majority of respondents (49%), do not routinely communicate directly with slaughter personnel who are often seasonal workers coming from outside Sweden. Moreover, olfaction and haptics could be considered naturally impractical with remote technologies. The study also finds that respondents from different administrative units and job titles have different preferences for the features of remote MI. Respondents from the headquarter generally have higher preferences for connectivity than respondents from other units. Additionally, respondents with more hands-on experience in MI, such as Official Veterinarians, tend to rate security issues higher than respondents with leading or support roles. Overall, it seems possible to meet the control staff expectations and preferences regarding the prerequisites of remote MI by legal and technical adaptations needed for this type of control flexibility.

Optimizing community science contributions in ecology: A case study on Zooniverse's ‘Chicago wildlife watch’

Public participation in research, or community science (CS), has an important role in advancing ecological research, especially data processing. CS contributions to camera trap studies have supported wildlife conservation through the rapid processing of images and videos. However, more studies are needed to quantify the accuracy and efficiency of CS participation. We used a case study from Chicago Wildlife Watch, a Zooniverse project, to explore variability in image classification accuracy and assess efficiency of responsive retirement rules which dictate how many times an image is viewed and annotated. We found that CS participants were highly accurate when classifying empty (96.0 %) and commonly photographed species in our study area (60.14 % across all species). User agreement on species images most impacted classification accuracy, though accuracy was higher for those containing larger species and those annotated by more engaged participants. With respect to efficiency, we found that three consecutive ‘empty’ classifications from participants led to over 95 % classification accuracy in empty images and if 7 participants agreed on a species present in an image, they were accurate 98 % of the time, on average. These results further support the value of CS in ecological research and the value of applying unique project designs which consider occurrence of regional species and field systems (e.g. camera placement or ecosystem). Given these results, we encourage scientists to continue applying quantitative techniques to custom design projects to effectively use CS participants' time and maximize data accuracy.

Leveraging Swarm Intelligence for Optimal Thermal Camera and Sensor Placement in Industrial Environments

This research addresses the sensor placement optimization problem (SPOP) in the industrial sector, aiming to enhance operational efficiency and safety through the strategic deployment of sensors. The focus is on optimizing the locations of thermal cameras and motion sensors, with a dual objective of maximizing coverage and minimizing redundancy in the production hall. To solve this challenge, a method based on the application of the nature-inspired bat algorithm was employed. The study reveals noteworthy findings, emphasizing the proficiency of the bat algorithm (BA) in optimizing the placement of thermal cameras and motion sensors. Numeric outcomes demonstrate the algorithm’s effectiveness in maximizing machine coverage while minimizing sensor usage within a real-world industrial environment. These results underscore the versatility and reliability of the BA, establishing it as a valuable tool for addressing complex optimization tasks in industrial settings.

Improving Gait Analysis Techniques with Markerless Pose Estimation Based on Smartphone Location.

Marker-based 3D motion capture systems, widely used for gait analysis, are accurate but have disadvantages such as cost and accessibility. Whereas markerless pose estimation has emerged as a convenient and cost-effective alternative for gait analysis, challenges remain in achieving optimal accuracy. Given the limited research on the effects of camera location and orientation on data collection accuracy, this study investigates how camera placement affects gait assessment accuracy utilizing five smartphones. This study aimed to explore the differences in data collection accuracy between marker-based systems and pose estimation, as well as to assess the impact of camera location and orientation on accuracy in pose estimation. The results showed that the differences in joint angles between pose estimation and marker-based systems are below 5°, an acceptable level for gait analysis, with a strong correlation between the two datasets supporting the effectiveness of pose estimation in gait analysis. In addition, hip and knee angles were accurately measured at the front diagonal of the subject and ankle angle at the lateral side. This research highlights the significance of careful camera placement for reliable gait analysis using pose estimation, serving as a concise reference to guide future efforts in enhancing the quantitative accuracy of gait analysis.

Complex Background Removal Method for Video of an Inclined Cable Based on UAV Detection of Structural Vibration Frequencies

The safety of inclined cables is fundamental to the integrity of cable-stayed bridges. The vibrational frequencies of these cables form the foundation for assessing the cable force. Traditional contact measurement methods necessitate the installation of sensors on each cable, incurring substantial costs. In scenarios where camera placement adjacent to an inclined cable is impractical, noncontact approaches such as video capture via unmanned aerial vehicles prove effective. However, unmanned aerial vehicle-captured videos present a challenge due to their complex background, impeding cable feature recognition. In our study, we initially utilized the Region Growing algorithm for background subtraction. To enhance this method, we integrated it with the unique structural characteristics of cables, leading to the creation of the RGv2 algorithm. This novel algorithm offers increased processing speed and improved accuracy. Furthermore, we combined our method with empirical mode decomposition for effective detection of cable frequency characteristics. We also implemented a hybrid method, combining the K-Means and line segment detector algorithms with empirical mode decomposition. Compared to deep learning techniques for background subtraction, our proposed method demonstrates superior computational efficiency and promising potential for measuring vibrational frequencies of inclined cables.

Comparison of three indirect methods for density estimation of the wild boar (Sus scrofa) in different habitats in South Korea

Increasing human-wild boar conflicts in South Korea have led to a demand for effective management strategies. Absolute abundance, rather than relative indices, is needed for the long-term monitoring and population control of wild boars. Indirect methods for density estimation have become increasingly popular because they are cost-effective and do not have the risk of capture probability bias. We compared three indirect methods, including the non-invasive capture-recapture model (NICRM), random encounter model (REM), and fecal standing crop (FSC), in two different sites characterized by specific habitats (urban and agricultural environments). NICRM and REM reflected population fluctuation and hunting intensity assumptions at both sites; however, FSC did not reflect the latter. While using NICRM, efforts are needed for achieving a low genotyping error rate; this model would achieve more reliable results in low-density areas. REM with accurate parameter information (i.e., daily range, detection zone, and camera placement) could be the most effective density estimation method for long-term monitoring in South Korean environments. Conversely, FSC may not be recommended because of many factors, such as decomposition rate, rainfall, biased distribution of feces that might affect pellet groups. Additionally, the density estimates from this study can provide information for developing effective management strategies in South Korean environments.

A Continuous Camera Placement Optimization Model for Surround View

A Continuous Camera Placement Optimization Model for Surround View

Thermal-based gender recognition using drones: advancing biometric recognition in challenging outdoor environments

While biometric recognition typically uses features such as face, fingerprint, and iris to identify individuals, this study focuses on utilising specific characteristics to identify gender. The aim of this article is to propose a procedure for gender recognition under specific conditions. The specific condition addressed is outdoor area monitoring, which presents challenges such as varying lighting conditions and limited camera placement options. To tackle this, a proposed procedure utilises thermal images captured by the drone equipped with a thermal camera. The advantage of thermal images is their independence from ambient light conditions. The captured images are resized and processed using convolutional neural networks (CNNs) (AlexNet, VGG-16, VGG-19) for feature extraction and binary classification. A freely available database of thermal face images is used for training the CNNs, while a own created dataset of thermal images obtained by the drone is used for testing. The findings indicate that the optimised CNNs achieve classification accuracies of 82.4% (VGG-16), 82.9% (AlexNet), and 85.5% (VGG-19). The original contribution of this study lies in demonstrating the suitability of face thermal images obtained through drones for gender recognition purposes.

Improving Surveillance in a Barangay: A Study on Assessing Needs for Designing Optimal Closed-Circuit Television Camera Placement

This study aimed to conduct a needs assessment in order to design a CCTV camera placement plan in a barangay to enhance community safety and security. Employing a descriptive research design, the study involved 300 randomly selected respondents from a barangay in Talugtug, Nueva Ecija, Philippines. The results of the needs assessment underscored the importance of developing a CCTV camera placement plan for the barangay. The researcher proposed to develop a plan that aims to provide measures to improve safety and security within the community. Based on the needs assessment that has been conducted, several recommendations were drawn. Firstly, it was strongly advised to design a CCTV camera placement plan in the barangay. A follow-up study may be conducted focusing on this aspect. Future researchers must strategically place the CCTV in the area to optimize its full potential for securing the community. Secondly, community engagement and collaboration were highlighted as crucial factors for successful implementation, emphasizing the importance of involving community members, stakeholders, and educational institutions in the planning process. Thus, when designing a strategic CCTV placement plan, the involvement of various stakeholders is highly encouraged. Further, allocating resources for installation, maintenance, and monitoring was also proposed to ensure the sustainability and effectiveness of the surveillance system. Lastly, continuous evaluation and improvement of the CCTV camera placement plan when implemented is highly recommended, emphasizing the need for regular reviews, resident feedback, and performance monitoring to optimize the system's functionality. These recommendations provide valuable guidance for barangay officials in their pursuit of enhanced safety and security. By implementing the proposed plan that may be developed through this study and considering the input of the community, the barangay can create a safer environment and promote a sense of security among its residents.

Challenges of Engineering Applications of Descriptive Geometry

Descriptive geometry has indispensable applications in many engineering activities. A summary of these is provided in the first chapter of this paper, preceded by a brief introduction into the methods of representation and mathematical recognition related to our research area, such as projection perpendicular to a single plane, projection images created by perpendicular projection onto two mutually perpendicular image planes, but placed on one plane, including the research of curves and movements, visual representation and perception relying on a mathematical approach, and studies on toothed driving pairs and tool geometry in order to place the development presented here among them. As a result of the continuous variability of the technological environment according to various optimization aspects, the engineering activities must also be continuously adapted to the changes, for which an appropriate approach and formulation are required from the practitioners of descriptive geometry, and can even lead to improvement in the field of descriptive geometry. The imaging procedures are always based on the methods and theorems of descriptive geometry. Our aim was to examine the spatial variation in the wear of the tool edge and the machining of the components of toothed drive pairs using two cameras. Resolving contradictions in spatial geometry reconstruction research is a constant challenge, to which a possible answer in many cases is the searching for the right projection direction, and positioning cameras appropriately. A special method of enumerating the possible infinite viewpoints for the reconstruction of tool surface edge curves is presented in the second part of this paper. In the case of the monitoring the shape geometry, taking into account the interchangeability of the projection directions, i.e., the property of symmetry, all images made from two perpendicular directions were taken into account. The procedure for determining the correct directions in a mathematically exact way is also presented through examples. A new criterion was formulated for the tested tooth edge of the hob to take into account the shading of the tooth next to it. The analysis and some of the results of the Monge mapping, suitable for the solution of a mechanical engineering task to be solved in a specific technical environment, namely defining the conditions for camera placements that ensure reconstructibility are also presented. Taking physical shadowing into account, conclusions can be drawn about the degree of distortion of the machined surface from the spatial deformation of the edge curve of the tool reconstructed with correctly positioned cameras.

Warehouse Small Cargo-carrying UAV Design and Environmental T265 Camera Placement Angle Study

The Intel RealSense Tracking Camera T265 is a tracking camera that uses its own Vi-Slam algorithm to output horizontal and vertical coordinates, which has a wide range of applications in drones, unmanned boats, and unmanned vehicles. In this paper, we utilize the T265 and the Pixhawk4 (PX4) flight controller to build a Robotics Operating System (ROS)-based, fixed-point cruise-capable, self-taking-off and landing unmanned aerial vehicle (UAV) for cargo loading. The T265 is a fisheye black and white camera with powerful visual simultaneous localization and mapping (Slam) localization and a large visual range. The T265 features the Movidius Myriad 2 visual processing unit. Slam construction based on the comparison of feature points to output coordinates. Nevertheless, when the environment has a single color and insufficient feature contrast, it is easy to cause a SLAM error, leading to drifting of the drone's coordinates, which is very dangerous. It is easy to injure drone operators and other pedestrians accidentally, and at the same time, it is often accompanied by drone crashes that cause economic losses. We experimented with placing the T265 camera at multiple angles to test the best placement angle for more accurate drone positioning. The article also describes the mechanical mechanism design, hardware and software design of the cargo UAV, the optimal placement angle was verified in the environment described in the paper.