8,111 research outputs found
Structured Light-Based 3D Reconstruction System for Plants.
Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance
Monitoring water-soil dynamics and tree survival using soil sensors under a big data approach
ArticleThe high importance of green urban planning to ensure access to green areas requires
modern and multi-source decision-support tools. The integration of remote sensing data and sensor
developments can contribute to the improvement of decision-making in urban forestry. This study
proposes a novel big data-based methodology that combines real-time information from soil sensors
and climate data to monitor the establishment of a new urban forest in semi-arid conditions. Water-soil
dynamics and their implication in tree survival were analyzed considering the application of di erent
treatment restoration techniques oriented to facilitate the recovery of tree and shrub vegetation in
the degraded area. The synchronized data-capturing scheme made it possible to evaluate hourly,
daily, and seasonal changes in soil-water dynamics. The spatial variation of soil-water dynamics
was captured by the sensors and it highly contributed to the explanation of the observed ground
measurements on tree survival. The methodology showed how the e ciency of treatments varied
depending on species selection and across the experimental design. The use of retainers for improving
soil moisture content and adjusting tree-watering needs was, on average, the most successful
restoration technique. The results and the applied calibration of the sensor technology highlighted the
random behavior of water-soil dynamics despite the small-scale scope of the experiment. The results
showed the potential of this methodology to assess watering needs and adjust watering resources to
the vegetation status using real-time atmospheric and soil datainfo:eu-repo/semantics/publishedVersio
Review of Calibration Methods for Scheimpflug Camera
The Scheimpflug camera offers a wide range of applications in the field of typical close-range photogrammetry, particle image velocity, and digital image correlation due to the fact that the depth-of-view of Scheimpflug camera can be greatly extended according to the Scheimpflug condition. Yet, the conventional calibration methods are not applicable in this case because the assumptions used by classical calibration methodologies are not valid anymore for cameras undergoing Scheimpflug condition. Therefore, various methods have been investigated to solve the problem over the last few years. However, no comprehensive review exists that provides an insight into recent calibration methods of Scheimpflug cameras. This paper presents a survey of recent calibration methods of Scheimpflug cameras with perspective lens, including the general nonparametric imaging model, and analyzes in detail the advantages and drawbacks of the mainstream calibration models with respect to each other. Real data experiments including calibrations, reconstructions, and measurements are performed to assess the performance of the models. The results reveal that the accuracies of the RMM, PLVM, PCIM, and GNIM are basically equal, while the accuracy of GNIM is slightly lower compared with the other three parametric models. Moreover, the experimental results reveal that the parameters of the tangential distortion are likely coupled with the tilt angle of the sensor in Scheimpflug calibration models. The work of this paper lays the foundation of further research of Scheimpflug cameras
Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey
Growing progress in sensor technology has constantly expanded the number and
range of low-cost, small, and portable sensors on the market, increasing the
number and type of physical phenomena that can be measured with wirelessly
connected sensors. Large-scale deployments of wireless sensor networks (WSN)
involving hundreds or thousands of devices and limited budgets often constrain
the choice of sensing hardware, which generally has reduced accuracy,
precision, and reliability. Therefore, it is challenging to achieve good data
quality and maintain error-free measurements during the whole system lifetime.
Self-calibration or recalibration in ad hoc sensor networks to preserve data
quality is essential, yet challenging, for several reasons, such as the
existence of random noise and the absence of suitable general models.
Calibration performed in the field, without accurate and controlled
instrumentation, is said to be in an uncontrolled environment. This paper
provides current and fundamental self-calibration approaches and models for
wireless sensor networks in uncontrolled environments
Evaluation of spatial, radiometric and spectral Thematic Mapper performance for coastal studies
On 31 March 1983, the University of Delaware's Center for Remote Sensing initiated a study to evaluate the spatial, radiometric and spectral performance of the LANDSAT Thematic Mapper for coastal and estuarine studies. The investigation was supported by Contract NAS5-27580 from the NASA Goddard Space Flight Center. The research was divided into three major subprojects: (1) a comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in Chesapeake Bay; (2) remote sensing of submerged aquatic vegetation - a radiative transfer approach; and (3) remote sensing of coastal wetland biomass using Thematic Mapper wavebands
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Quantifying Physical Activity in Young Children Using a Three-Dimensional Camera
The purpose of this study was to determine the feasibility and validity of using three-dimensional (3D) video data and computer vision to estimate physical activity intensities in young children. Families with children (2–5-years-old) were invited to participate in semi-structured 20-minute play sessions that included a range of indoor play activities. During the play session, children’s physical activity (PA) was recorded using a 3D camera. PA video data were analyzed via direct observation, and 3D PA video data were processed and converted into triaxial PA accelerations using computer vision. PA video data from children (n = 10) were analyzed using direct observation as the ground truth, and the Receiver Operating Characteristic Area Under the Curve (AUC) was calculated in order to determine the classification accuracy of a Classification and Regression Tree (CART) algorithm for estimating PA intensity from video data. A CART algorithm accurately estimated the proportion of time that children spent sedentary (AUC = 0.89) in light PA (AUC = 0.87) and moderate-vigorous PA (AUC = 0.92) during the play session, and there were no significant differences (p \u3e 0.05) between the directly observed and CART-determined proportions of time spent in each activity intensity. A computer vision algorithm and 3D camera can be used to estimate the proportion of time that children spend in all activity intensities indoors
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