Forward Intersection Research Articles

Behaviors of pedestrians on streets with roadside strips

Pedestrian behaviors in natural settings have been investigated mainly on roads with sidewalks or the corridors outside or inside buildings. The present study examined pedestrian behaviors on roads with roadside strips, which are popular in Japanese local areas. The purpose of the study was to investigate pedestrian behaviors and the factors affecting them. Observations were made at two single-lane streets in Tokyo with 0.9 m and 0.5 m roadside strips. A total of 2,476 pedestrians were observed for 2 days (1 weekday, 1 weekend day) in each location. Walking with traffic was more popular (61%) than walking against traffic. People seemed to walk either side of the street depending on their turn direction at the forward intersection. Illegal behavior of walking into the roadway was also observed in 46% of pedestrians. This behavior was more likely to appear on the streets with narrower roadside strips and when people walked in a group. As expected, males, young and mature adults, and single pedestrians walked faster than females, children and senior adults, and pedestrians in a group. When a female and a male walked abreast, males tended to reduce their walking speed considerably and walk on the roadway side (62%), taking care of females. Similar positional consideration for a vulnerable partner was also found in parent–child pairs. It was concluded that people are likely to violate traffic law if the violation serves a purpose, and they tend to behave altruistically towards others, even if there is no relevant rule.

DSM Extraction Based on Gaofen-6 Satellite High-Resolution Cross-Track Images with Wide Field of View.

Digital Surface Model (DSM) is a three-dimensional model presenting the elevation of the Earth's surface, which can be obtained by the along-track or cross-track stereo images of optical satellites. This paper investigates the DSM extraction method using Gaofen-6 (GF-6) high-resolution (HR) cross-track images with a wide field of view (WFV). To guarantee the elevation accuracy, the relationship between the intersection angle and the overlap of the cross-track images was analyzed. Cross-track images with 20-40% overlaps could be selected to conduct DSM extraction. First, the rational function model (RFM) based on error compensation was used to realize the accurate orientation of the image. Then, the disparity map was generated based on the semi-global block matching (SGBM) algorithm with epipolar constraint. Finally, the DSM was generated by forward intersection. The GF-6 HR cross-track images with about 30% overlap located in Taian, Shandong Province, China, were used for DSM extraction. The results show that the mountainous surface elevation features were retained completely, and the details, such as houses and roads, were presented in valleys and urban areas. The root mean square error (RMSE) of the extracted DSM could reach 6.303 m, 12.879 m, 14.929 m, and 19.043 m in valley, ridge, urban, and peak areas, respectively. The results indicate that the GF-6 HR cross-track images with a certain overlap can be used to extract a DSM to enhance its application in land cover monitoring.

An Improved Intersection Method for Positioning and Its Application to Dalk Glacier, East Antarctica

Stake measurement is a significant ground-observation method used to monitor glacier dynamics in the cryosphere and validate the reliability of remotely sensed investigations. However, some stake observation records obtained by total stations have not been efficiently utilized via the classic forward intersection method. The forward intersection method requires a pair of cognominal observation records and cannot function if stakes are only observed from one control point at a stake measurement, which commonly occurs in measurements. Therefore, we propose an improved intersection method that combines stake trajectories and sightlines, the trajectory-sightline intersection method, which requires only a single observation record. In the processing of stake identification, location and elevation from the trajectory-sightline intersection method are constrained by the velocity and surface altitude of the glacier. Then, the trajectory-sightline intersection method is applied to the stake measurement of Dalk Glacier in East Antarctica. The results show that the trajectory-sightline intersection method extracted an additional 44 intersections, thus increasing the data utilization ratio by 20.35%. Moreover, leave-p-out cross-validation indicated that the trajectory-sightline intersection method, with an average offset of 0.88±0.54 m in the horizontal position and 0.26±0.12 m at the elevation, has similar accuracy to the differential global positioning system (DGPS) applied to Livingston Island. The ice flow velocities of Dalk Glacier calculated from trajectory-sightline intersections agree with those from forward intersections (the mean velocity difference is 0.47 m·year−1). Therefore, the trajectory-sightline intersection method is an effective method for improving data utilization and obtaining stake locations and glacier velocities.

Research on high precision measurement of head position and posture

For the safety of pilots, it is necessary to explore the change process of ATD head spatial position and posture in the dynamic impact test of driver's seat. Therefore, a comprehensive position and posture solution method was proposed, which mainly including bundle adjustment method, forward intersection method and feature line projection method. This method achieves the high precision of the ATD head position and posture measurement requirements, and its measurement accuracy reaches the level of mm and degree respectively.

Position Estimation of Forest Fires using an Infrared Camera Based on Pan Tilt Servo

Forest fires are often enlarged over extended periods of time, but if they are detected through image-based real-time monitoring, this would shorten the response time of fire fighters, thereby preventing great damage. When a forest fire occurs, it is often difficult to access the area and to accurately identify the location of its occurrence through monitoring images only. To overcome these problems, this paper proposes a method of detecting forest fires using infrared cameras and estimating the location of the forest fire by applying the space forward intersection method. Additionally, practicality verification was conducted through an outdoor ignition experiment, and the measurement accuracy of distance was compared.

COOPERATIVE IMAGE ORIENTATION CONSIDERING DYNAMIC OBJECTS

Abstract. In the context of image orientation, it is commonly assumed that the environment is completely static. This is why dynamic elements are typically filtered out using robust estimation procedures. Especially in urban areas, however, many such dynamic elements are present in the environment, which leads to a noticeable amount of errors that have to be detected via robust adjustment. This problem is even more evident in the case of cooperative image orientation using dynamic objects as ground control points (GCPs), because such dynamic objects carry the relevant information. One way to deal with this challenge is to detect these dynamic objects prior to the adjustment and to process the related image points separately. To do so, a novel methodology to distinguish dynamic and static image points in stereoscopic image sequences is introduced in this paper, using a neural network for the detection of potentially dynamic objects and additional checks via forward intersection. To investigate the effects of the consideration of dynamic points in the adjustment, an image sequence of an inner-city traffic scenario is used; image orientation, as well as the 3D coordinates of tie points, are calculated via a robust bundle adjustment. It is shown that compared to a solution without considering dynamic points, errors in the tie points are significantly reduced, while the median of the precision of all 3D coordinates of the tie points is improved.

GENERATION OF REFERENCE VEHICLE TRAJECTORIES IN REAL-WORLD SITUATIONS USING AERIAL IMAGERY FROM A HELICOPTER

Abstract. Highly accurate reference vehicle trajectories are required in the automotive domain e. g. for testing mobile GNSS devices. Common methods used to determine reference trajectories are based on the same working principles as the device under test and suffer from the same underlying error problems. In this paper, a new method to generate reference vehicle trajectories in real-world situations using simultaneously acquired aerial imagery from a helicopter is presented. This method requires independent height information which is coming from a LIDAR DTM and the relative height of the GNSS device. The reference trajectory is then derived by forward intersection of the vehicle position in each image with the DTM. In this context, the influence of all relevant error sources were analysed, like the error from the LIDAR DTM, from the sensor latency, from the semi-automatic matching of the vehicle marking, and from the image orientation. Results show that the presented method provides a tool for creating reference trajectories that is independent of the GNSS reception at the vehicle. Moreover, it can be demonstrated that the proposed method reaches an accuracy level of 10 cm, which is defined as necessary for certification and validation of automotive GNSS devices.

A General Framework of Remote Sensing Epipolar Image Generation

Epipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo properties, in this paper, we propose a general framework to generate epipolar images for both in-track and cross-track stereo images. We first investigate the theoretical epipolar constraints of single-sensor and multi-sensor images and then introduce the proposed framework in detail. Considering large elevation changes in mountain areas, the publicly available digital elevation model (DEM) is applied to reduce the initial offsets of two stereo images. The left image is projected into the image coordinate system of the right image using the rational polynomial coefficients (RPCs). By dividing the raw images into several blocks, the epipolar images of each block are parallel generated through a robust feature matching method and fundamental matrix estimation, in which way, the horizontal disparity can be drastically reduced while maintaining negligible vertical disparity for epipolar blocks. Then, stereo matching using the epipolar blocks can be easily implemented and the forward intersection method is used to generate the digital surface model (DSM). Experimental results on several in-track and cross-track images, including optical-optical, SAR-SAR, and SAR-optical pairs, demonstrate the effectiveness of the proposed framework, which not only has obvious advantages in mountain areas with large elevation changes but also can generate high-quality epipolar images for flat areas. The generated epipolar images of a ZiYuan-3 pair in Songshan are further utilized to produce a high-precision DSM.

Adaptive Quasi-Monte Carlo method for nonlinear function error propagation and its application in geodetic measurement

The standard deviation of the nonlinear functional value can be obtained by the law of covariance propagation. Existing covariance propagation methods of the nonlinear model contain the following problems: the approximate function method requires complicated derivative operation; the Monte Carlo method has a high simulated burden and low convergence effectiveness. To overcome these disadvantages, we introduce the Quasi-Monte Carlo (QMC) method and design the implementation process of the QMC method for covariance propagation with independent or correlated observations. Considering that the QMC method cannot balance the number of simulations and the accuracy of the results, a novel QMC algorithm for small numbers of batches simulation is proposed, namely, Adaptive Quasi-Monte Carlo (AQMC). The QMC method and the AQMC algorithm are applied in the forward intersection and covariance propagation of the GNSS baseline vector in geodetic measurement. The results verify the effectiveness of the QMC method and the AQMC algorithm. Compared with the adaptive Monte Carlo method, the AQMC method can improve the computational efficiency by almost 84.4%. The proposed approach provides a new idea for the covariance propagation of the nonlinear model.

Application of BeiDou Satellite in Frontier Monitoring and Defense System

Aiming at the problem of illegal border crossings on plateaus and mountainous borders, this paper proposes a frontier monitoring and defense system built with BeiDou satellite positioning, timing, navigation, short message communication and other functions to scan and monitor the border in real time. The rapid target positioning method of BeiDou static and dynamic monitoring point fusion of forward intersection and trigonometric leveling technique is presented. Meanwhile, crossing alarm and defense system are connected. For those who enter or cross the boundary illegally, we adopt measures such as warnings, shouting to drive away and positioning and arresting. So as to improve the informatization level of control of frontier and ensure the safety of frontier management personnel.

Accuracy analysis of dam deformation monitoring and correction of refraction with robotic total station.

Robotic total stations have been widely used in continuous automatic monitoring of dam deformations. In this regard, monitoring accuracy is an important factor affecting deformation analysis. First the displacements calculation methods for dam deformation monitoring with total stations are presented, and the corresponding mean square error formulas are derived. Then for errors caused by atmospheric refraction, two correction methods are described. Simulations were conducted to compare the displacement accuracy calculated through different methods. It indicated that the difference between polar coordinate method and forward intersection is less than 0.5mm within around 400m’ monitoring range, and in such cases, the polar coordinate method is preferred, as only one total station is required. Refraction correction tests with observations from two dams demonstrated that both correction methods could effectively enhance the monitoring accuracy. For observation correction, correction through the closest reference point achieves better correction results.

Introduction of All-Around 3D Modeling Methods for Investigation of Plants

Digital image phenotyping has become popular in plant research. Plants are complex in shape, and occlusion can often occur. Three-dimensional (3D) data are expected to measure the morphological traits of plants with higher accuracy. Plants have organs with flat and/or narrow shapes and similar component structures are repeated. Therefore, it is difficult to construct an accurate 3D model by applying methods developed for industrial materials and architecture. Here, we review noncontact and all-around 3D modeling and configuration of camera systems to measure the morphological traits of plants in terms of system composition, accuracy, cost, and usability. Typical noncontact 3D measurement methods can be roughly classified into active and passive methods. We describe their advantages and disadvantages. Structure-from-motion/multi-view stereo (SfM/MVS), a passive method, is the most frequently used measurement method for plants. It is described in terms of “forward intersection” and “backward resection.” We recently developed a novel SfM/MVS approach by mixing the forward and backward methods, and we provide a brief overview of our approach in this paper. While various fields are adopting 3D model construction, nonexpert users struggle to use them and end up selecting inadequate methods, which lead to model failure. We hope that this review will help users who are considering starting to construct and measure 3D models.

Approaches for exploration of improving multi-slice mapping via forwarding intersection based on images of UAV oblique photogrammetry

It is quite challenging to improve the accuracy of the measurement point coordinate when using the double forward intersection method to measure the coordinates of ground objects in the traditional digital photogrammetry system. In this paper, a method is proposed to improve the coordinate accuracy of measuring points using multi-slice forward intersection mapping. The intersection images are provided for multiple mapping through the unmanned aerial vehicle (UAV) oblique photogrammetry system to obtain high overlap and multi-angle oblique image data. The experimental results show that the accuracy qualification rate of marking points is high. The total rate of standard-reaching is up to 45.14%. The proposed method can improve the coordinate accuracy of aero photogrammetry by 8.7% using multi-view images obtained by UAV oblique photogrammetry.

OPTIMIZED DETERMINATION OF 3D COORDINATES IN THE SURVEY OF INACCESSIBLE POINTS OF BUILDINGS - EXAMPLE OF APPLICATION IMPLEMENTED IN FREE SOFTWARE

Abstract: The forward intersection method is already widely used in the geodetic survey of coordinates of inaccessible points, especially when only angle measurements are available, in this case, also called the triangulation method. However, the mathematical solution of the 3D forward intersection with the analytical definition of spatial lines, resolved by the Minimum Distances Method, is still not widespread in the academic and professional environment. This mathematical modeling determines the 3D coordinates of a point located in the middle of the minimum distance between two or more spatial lines, which spatially "intersect" towards the observation point. This solution is more accurate than others presented in the literature because it simultaneously solves the problem of 3D determination of a point by the method of least squares, in addition to providing an estimate of the coordinate precision, which are inherent to the adjustment. This work, therefore, has the objective of explaining the Minimum Distances Method for the spatial intersection of targeted measurements with a Total Station from two or more known observation points for the 3D determination of inaccessible points located in corners of buildings. For the analysis of the method, a Python tool was developed for QGIS that calculates the 3D coordinates and generates the adjustment processing report, being applied with real observations of the Geodetic survey of the SUDENE building, in Recife-PE. The methodology developed in this work proved to be suitable for measurements of large structures, achieving spherical precision better than ±1.0 cm, following the Brazilian standards for urban cadastre.

The features of application of different systems of orientation angles at the processing of aerospace images

The angular elements of external orientation characterize the position of a shooting camera relative to the coordinate system in which the spatial coordinates of the points of the object under study are determined from the processing of its images. In many cases of aerial photography, e.g. shooting from an unmanned aerial vehicle, as well as in the case of space survey, the values of the orientation angles could be very significant. This paper presents the results of numerical experiments for five different systems of external orientation angles (Euler angles). The studies were performed using the condition of complanarity, which is the basis of space forward intersection. For a space forward intersection, a model of errors in determining spatial coordinates for five systems of shooting camera orientation angles has been developed. In the numerical experiments, the general case of aerial photography from an unmanned aerial vehicle and of space survey of the Earth were simulated. By comparing the root-mean-square errors (RMSE) in determining the spatial coordinates obtained using the studied systems of external orientation angles, the features of the use of these systems of orientation angles were revealed. The results of the research will allow to determine the spatial coordinates of the points of the studied objects with a greater degree of reliability by photogrammetry methods.

Self-registration shape measurement based on fringe projection and structure from motion.

As an accurate and efficient shape measurement method, fringe-projection-based three-dimensional (3D) reconstruction has been extensively studied. However, patchwise point cloud registration without extra assistance is still a challenging task. We present a flexible and robust self-registration shape measurement method based on fringe projection and structure from motion (SfM). Other than ordinary structured-light measurement devices in which the camera and the projector are rigidly connected together, the camera and the projector in our method can be moved independently. An image-capturing scheme and underlying image-matching strategy are proposed. By selectively utilizing some sparse correspondence points across the fringe images as virtual markers, the global positions of the camera and the projector corresponding to each image are calculated and optimized under the framework of SfM. Dense global 3D points all over the object surface are finally calculated via forward intersection. Experimental results on different objects demonstrate that the proposed method can obtain a self-registered 3D point cloud with comparable accuracy to the state-of-the-art techniques by using only one camera and one projector, requiring no post-registration procedures and no assistant markers.

Optimal selection of virtual control points with planar constraints for large‐scale block adjustment of satellite imagery

AbstractIn large‐scale block adjustment of high‐resolution satellite imagery (HRSI) without ground control points (GCPs), the selection of virtual control points (VCPs) is an important factor in determining the block adjustment accuracy. The traditional VCP generation method is based on a regular grid and uses the initial rational polynomial coefficient (RPC) files but without considering topographic factors. To further improve the accuracy, this paper proposes an approach for the optimal selection of VCPs with planar constraints, which ensures that the VCPs are mostly in areas with small elevation differences and are not influenced by vegetation and buildings. A three‐step approach generates the 3D coordinates of tie points based on forward intersection, calculates their mean values and finally selects optimal VCPs using a threshold value. Experiments conducted using ZY3‐01 satellite images show the accuracy of the proposed method without GCPs outperforms the existing method.

LUNAR TERRAIN RECONSTRUCTION FROM MULTI-VIEW LROC NAC IMAGES BASED ON SEMI-GLOBAL MATCHING IN OBJECT SPACE

Abstract. Most of the lunar surface area has been observed from different viewing conditions thanks to the on-orbit work of lunar orbiters, a large amount of images are available for photogrammetric three-dimensional mapping, which is an important issue for lunar exploration. Theoretically, multi-view images contain more information than a single stereo pair and can get better 3D mapping results. In this paper, the semi-global matching method is applied to the object space, and the steps of cost calculation, cost aggregation, and elevation calculation are performed to obtain the three-dimensional coordinates directly. Compared with the traditional image-based semi-global matching method, the object-based semi-global method is more easily extended to multi-view images, which is beneficial for applying multi-view image information. In addition, it does not require steps such as stereo rectification and forward intersection, that is, the overall pipeline is more elegant. Using the LRO NAC images covering Apollo 11 landing area as the experimental data, the result shows that the object-based semi-global matching is competent for the multi-view image matching and the multi-view image result achieves higher accuracy and more details than the single stereo pair. Furthermore, the experimental results of Zhinyu crater data show that this method can also alleviate the uncertainty of the lunar orbiter's positioning to some extent.

OPTIMIZATION ALGORITHM OF TILTED IMAGE MATCHING BASED ON ADAPTIVE INITIAL OBJECT ASPECT

Abstract. When adopting the matching method of the least squares image based on object-patch to match tilted images, problems like the low degree of connection points for images with the discontinuity of depth or the discrepancy in elevation or low availability of aerotriangulation points would frequently appear. To address such problems, a tilted-image-matching algorithm based on an adaptive initial object-patch is proposed by this paper. By means of the existing initial values of the interior and exterior orientation elements of the tilted image and the information of object points generated in the matching process, the algorithm takes advantage of the method of multi-patch forward intersection and object variance partition so as to adaptively calculate the elevation of the object-patch and the initial value of the normal vector direction angle. Furthermore, this algorithm aims to solve the problem of difficulties in matching the tilted image with its corresponding points brought about by the low accuracy of the initial value of the tilted image when adopting the matching method of the least squares image based on object-patch to match the tilted image with high discrepancy in elevation. We adopt the algorithm as proposed in this paper and the least squares image matching method in which the initial state of the object-patch is horizontal to the object-patch respectively to conduct the verification process of comparing and matching two groups of tilted images. Finally, the effectiveness of the algorithm as proposed in this paper is verified by the testing results.

ACCURATE REGISTRATION OF AERIAL IMAGES AND ALS-POINTCLOUD VIA AUTOMATED JUNCTION MATCHING AND PLANAR CONSTRAINTS

Abstract. Accurate geometric registration of images and pointclouds is the key step of many 3D-reconstruction or 3D-sensing tasks. In this paper, a novel L-junction based approach is proposed for semi-automatic accurate registration of aerial images and the airborne laser scanning (ALS) point-cloud in urban areas. The approach achieves accurate registration by associating the LiDAR points with the local planes extracted via L-junction detection and matching from multi-view aerial images. An L-junction is an intersection of two line-segments. Through the forward intersection of multi-view corresponding L-junctions, an accurate local junction-plane can be obtained. In the proposed approach, L-junction is manually collected from one view on the flat object-surfaces like walls, roads, and roofs and then automatically matched to other views with the aid of epipolar-geometry and vanishing-point constraints. Then, a plane-constrained bundle block adjustment of the image-orientation parameters is conducted, where the LiDAR points are treated as reference data. The proposed approach was tested with two datasets collected in Guangzhou city and Ningbo city of China. The experimental results showed that the proposed approach had better accuracy than the closest-point based method. The horizontal/vertical registration RMS of the proposed approach reached 4.21cm/5.72cm in Guangzhou dataset and 4.46cm/4.34cm in Ningbo dataset, which was much less than the average LiDAR-point distance (over 25cm in both datasets) and was very close to the image GSDs (3.2cm in Guangzhou and 4.8cm in Ningbo) and the a-priori ranging accuracy of the ALS equipment (about 3cm).