Real-world Coordinates Research Articles

The 2011 Japan tsunami current velocity measurements from survivor videos at Kesennuma Bay using LiDAR

On March 11, 2011, a magnitude Mw 9.0 earthquake occurred off the coast of Japan's Tohoku region causing catastrophic damage and loss of life. The tsunami flow velocity analysis focused on two survivor videos recorded from building rooftops at Kesennuma Bay along Japan's Sanriku coast. A terrestrial laser scanner was deployed at the locations of the tsunami eyewitness video recordings. The tsunami current velocities through the Kesennuma Bay are determined in a four step process. The LiDAR point clouds are used to calibrate the camera fields of view in real world coordinates. The motion of the camera during recordings was determined. The video images were rectified with direct linear transformation. Finally a cross‐correlation based particle image velocimetry analysis was applied to the rectified video images to determine instantaneous tsunami flow velocity fields. The measured maximum tsunami height of 9 m in the Kesennuma Bay narrows were followed by maximum tsunami outflow currents of 11 m/s less than 10 minutes later.

A Space-Mapping Method for Object Location Estimation Adaptive to Camera Setup Changes for Vision-Based Automation Applications

A new space-mapping method for object location estimation, which is adaptive to camera setup changes, for use in various automation applications is proposed. The location of an object appearing in an image is estimated by mapping image coordinates of object points to corresponding real-world coordinates using a mapping table, which is constructed in two stages, with the first stage for establishing a basic table using bilinear interpolation in the camera manufacturing environment and the second for adapting the table to changes of camera heights and orientations in the application field. Analytic equations for table adaptation are derived by skillful utilization of both image formation and camera geometry properties. Good experimental results are shown to prove the feasibility of the proposed method.

Modelling and mapping third dimension in a spatial database

In this paper, an overview of phases for modelling and mapping third dimension of spatial objects in a database is presented based on a selected spatial database management system (DBMS). These phases include (1) defining a spatial reference system for representing three-dimensional (3D) objects with real-world coordinates, (2) geometric modelling of 3D objects in the database, (3) 3D spatial indexing for fast accessing/querying the 3D data, 3D spatial queries and representation of 3D data. Then, a case study is performed to assess needs, possibilities and potential limitations of 3D data modelling in the spatial database.

Flow measurements in sewers based on image analysis: automatic flow velocity algorithm

Discharges of combined sewer overflows (CSOs) and stormwater are recognized as an important source of environmental contamination. However, the harsh sewer environment and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. An in situ system for sewer water flow monitoring based on video images was evaluated. Algorithms to determine water velocities were developed based on image-processing techniques. The image-based water velocity algorithm identifies surface features and measures their positions with respect to real world coordinates. A web-based user interface and a three-tier system architecture enable remote configuration of the cameras and the image-processing algorithms in order to calculate automatically flow velocity on-line. Results of investigations conducted in a CSO are presented. The system was found to measure reliably water velocities, thereby providing the means to understand particular hydraulic behaviors.

Measuring propeller blade width using binocular stereo vision

Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previous techniques are usually time-consuming and erroneous due to a large number of points to be processed in blade width measurement. This paper proposes a new method of measuring blade width using two images acquired from different viewpoints of the same blade. And a new feature points matching approach for propeller blade image is proposed in stereo vision measurement. Based on these, pixel coordinates of contour points of the blade in two images are extracted and converted to real world coordinates by image algorithm and binocular stereo machine vision theory. Then, from the real world coordinates, the blade width at any position can be determined by simple geometrical method.

Stereoscopic motion analysis in densely packed clusters: 3D analysis of the shimmering behaviour in Giant honey bees.

BackgroundThe detailed interpretation of mass phenomena such as human escape panic or swarm behaviour in birds, fish and insects requires detailed analysis of the 3D movements of individual participants. Here, we describe the adaptation of a 3D stereoscopic imaging method to measure the positional coordinates of individual agents in densely packed clusters. The method was applied to study behavioural aspects of shimmering in Giant honeybees, a collective defence behaviour that deters predatory wasps by visual cues, whereby individual bees flip their abdomen upwards in a split second, producing Mexican wave-like patterns.ResultsStereoscopic imaging provided non-invasive, automated, simultaneous, in-situ 3D measurements of hundreds of bees on the nest surface regarding their thoracic position and orientation of the body length axis. Segmentation was the basis for the stereo matching, which defined correspondences of individual bees in pairs of stereo images. Stereo-matched "agent bees" were re-identified in subsequent frames by the tracking procedure and triangulated into real-world coordinates. These algorithms were required to calculate the three spatial motion components (dx: horizontal, dy: vertical and dz: towards and from the comb) of individual bees over time.ConclusionsThe method enables the assessment of the 3D positions of individual Giant honeybees, which is not possible with single-view cameras. The method can be applied to distinguish at the individual bee level active movements of the thoraces produced by abdominal flipping from passive motions generated by the moving bee curtain. The data provide evidence that the z-deflections of thoraces are potential cues for colony-intrinsic communication. The method helps to understand the phenomenon of collective decision-making through mechanoceptive synchronization and to associate shimmering with the principles of wave propagation. With further, minor modifications, the method could be used to study aspects of other mass phenomena that involve active and passive movements of individual agents in densely packed clusters.

2P1-C19 筋骨格ヒューマノイドの張力制御を利用した姿勢教示による物体拘束の獲得

Musculo-Skeletal Humanoid has a humanlike articular structure body and redundant actuators. Musculo-Skeletal Humanoid has advantage in touching objects by controlling its tendon tension flexibly. However, its own complex body structure makes it difficult to adjust humanoid's inner coordinate to real world coordinate. To solve the issue, we focused attention on the motion when human touch or trace objects. We apply a restrain condition estimation method using the musculo-skeletal humanoid's tension control to realize operating target objects. The aim of this paper is to show that Musculo-Skeletal Humanoid can generate motions associated with touching unknown objects by being taught poses.

Vision-based system for the control and measurement of wastewater flow rate in sewer systems

Combined sewer overflows and stormwater discharges represent an important source of contamination to the environment. However, the harsh environment inside sewers and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. In the following, we present and evaluate an in situ system for the monitoring of water flow in sewers based on video images. This paper focuses on the measurement of the water level based on image-processing techniques. The developed image-based water level algorithms identify the wall/water interface from sewer images and measure its position with respect to real world coordinates. A web-based user interface and a 3-tier system architecture enable the remote configuration of the cameras and the image-processing algorithms. Images acquired and processed by our system were found to reliably measure water levels and thereby to provide crucial information leading to better understand particular hydraulic behaviors. In terms of robustness and accuracy, the water level algorithm provided equal or better results compared to traditional water level probes in three different in situ configurations.

Inter-segmental coordination in progressions for the longswing on high bar

This study focused on identifying the most effective skill progression for developing the longswing on high bar in men's artistic gymnastics. Building on previous work by Irwin and Kerwin (2005), in which a method to rank progressions based on their angular kinematics was developed, this study aimed to use the method to quantify similarities in inter-segmental coordination between selected progressions and the longswing on high bar. Video images of four members of the UK men's national gymnastics squad performing three series of five longswings and eight progressions were recorded at 50 Hz. Two-dimensional direct linear transformation techniques were used to determine the real-world coordinates from the digitized data. Inter-segmental coordination of the hip and shoulder joints during the functional phases of the longswing was assessed using continuous relative phase. Similarity between the longswing and each progression was represented by a “specificity score”, which was also used to rank the progressions. Each progression's specificity score was calculated by combining a “difference score” (root mean squared difference between the continuous relative phase profiles of the longswing and the progression) and a “variability score” (standard deviation of the continuous relative phase profiles for each progression). The progressions that were most similar to the longswing included the looped bar longswing and layaway swing down (ranked 1st and 2nd), with specificity scores of 9% and 10% respectively. In contrast, the least similar progressions were the looped bar “no action” longswing (51%) and pendulum swing (63%) (ranked 7th and 8th). Establishing effective skill learning pathways is recognized as a key component of the coaching process and ranking progressions based on their specificity score provided a mechanism to identify progressions with similar inter-segmental coordination profiles to the key skill on the high bar, the longswing.

Neural mechanisms for timing visual events are spatially selective in real-world coordinates

It is generally assumed that perceptual events are timed by a centralized supramodal clock. This study challenges this notion in humans by providing clear evidence that visual events of subsecond duration are timed by visual neural mechanisms with spatially circumscribed receptive fields, localized in real-world, rather than retinal, coordinates.

A Comparison Between Stereo-Vision Techniques for the Reconstruction of 3-D Coordinates of Objects

This paper deals with the problems in setting up stereo-vision systems for contactless measurement of dimensional parameters in industrial environments. Two implicit calibration algorithms for the reconstruction of three-dimensional (3-D) real-world coordinates of objects from pairs of two-dimensional image coordinates have been implemented and compared. The former is based on a direct linear transformation, while the latter on an Artificial Neural Network (ANN). The results of the comparison made on artificial and real objects are finally reported in terms of statistical analysis of the reconstruction error

Real-time video content analysis tool for consumer media storage system

With the growing storage capacities of hard-disks and optical discs, large consumer video databases are gradually developing. The large effective storage capacity using compressed video leads to the application of fast storage and retrieval functions, to enable quick user-friendly searching for and access to specific parts of the video data. We explore the feasibility of a near real-time semantic sports video analyzer for an experimental consumer media server. This tool is able to automatically extract and analyze key events in a video sequence. The analyzer employs several visual cues and a model for real-world coordinates, so that key parameters (e.g. speed and position) of a player can be determined with sufficient accuracy. This special data can be stored as metadata, thereby facilitating intelligent searching of events. The tool consists of four processing steps: (1) playing frame detection, (2) court extraction, as well as a 3-D camera model, (3) player segmentation and tracking, and (4) event-based high-level analysis exploiting visual cues extracted in the real-world. Our system has been evaluated in a new distributed AV content analysis system for home entertainment. We show attractive experimental results indicating the system efficiency and classification skills, thereby offering new analysis and search/retrieval tools to the consumer

Design and development of automated 3D visual tracking system†

Camera‐based systems are frequently used to track moving objects which are in the field of their view. This paper describes design and development of a camerabased visual system that can constantly track a moving object without the necessity of calibrating the camera in real world coordinates. This reduces the complexity of the system and processing time due to unnecessary conversions and calibrations. The system consists of a two‐motor pan‐tilt camera driving mechanism, PCI image acquisition board, and PWM‐based DC‐motor driver board. It uses image processing techniques to identify and locate the object in the 3D scene and motion control algorithms to direct the camera towards the object. Thus the objective of the project is to develop a vision system and control algorithms which can be locked on a moving object within the field of its view. The developed software and related interface hardware monitor and control the motors in such a way that the moving object should always be located right at the center of the camera image plane. The system, in general, simulates the 3D motion of the human eye which always tends to focus on a moving object within the range of its view. It actually imitates the tracking ability of human eye.

A study of neural network based inverse kinematics solution for a three-joint robot

A neural network based inverse kinematics solution of a robotic manipulator is presented in this paper. Inverse kinematics problem is generally more complex for robotic manipulators. Many traditional solutions such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. In this study, a three-joint robotic manipulator simulation software, developed in our previous studies, is used. Firstly, we have generated many initial and final points in the work volume of the robotic manipulator by using cubic trajectory planning. Then, all of the angles according to the real-world coordinates ( x, y, z) are recorded in a file named as training set of neural network. Lastly, we have used a designed neural network to solve the inverse kinematics problem. The designed neural network has given the correct angles according to the given ( x, y, z) cartesian coordinates. The online working feature of neural network makes it very successful and popular in this solution.

Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation

In this paper, we present a new three-stage algorithm to calibrate roadside traffic management cameras and track vehicles to create a traffic speed sensor. The algorithm first estimates the camera position relative to the roadway using the motion and edges of the vehicles. Given the camera position, the algorithm then calibrates the camera by estimating the lane boundaries and the vanishing point of the lines along the roadway. The algorithm transforms the image coordinates from the vehicle tracker into real-world coordinates using our simplified camera model. We present results that demonstrate the ability of our algorithm to produce good estimates of the mean vehicle speed in a lane of traffic.

Pose estimation for planar structures

We address the registration problem for interactive AR applications. Such applications require a real-time registration process. Although the registration problem has received a lot of attention in the computer vision community, it's far from being solved. Ideally, an AR system should work in all environments without the need to prepare the scene ahead of time, and users should be able to walk anywhere they want. In the past, several AR systems have achieved accurate and fast tracking and registration, putting dots over objects and tracking the dots with a camera. We can also achieve registration by identifying features in the scene that we can carefully measure for real-world coordinates. However, such methods restrict the system's flexibility. Hence, we need to investigate registration methods that work in unprepared environments and reduce the need to know the objects' geometry in the scene. We propose an efficient solution to real-time camera tracking for scenes that contain planar structures. We can consider many types of scene with our method. We show that our system is reliable and we can use it for real-time applications. We also present results demonstrating real-time camera tracking on indoor and outdoor scenes.

Division of forest fuel type areas of Heilongjiang Province by using GIS

Eight factors, including forest coverage, fuel load, species composition, elevation, monthly mean temperature, monthly mean relative humidity, monthly mean wind velocity, and monthly mean precipitation of fire season, were considered and the methods of weight, the cumulative probability, ARC/INFO technique, and raster-to-vector conversion were adopted in division of forest fuel type area. Firstly, the electronic maps of forest distribution and administrative divisions were built, then overlaid and transformed to the real-world coordinates. Finally, the forest fuel type areas of Heilongjiang Province including 81 counties were divided into five grades, accounting for 16%, 17%, 17%, 11%, and 38% respectively. The grade I fuel type areas with highest fire danger rating mainly distributed on Daxing’anling Mountains, Xiaoxing’anling Mountains, and Zhangguangcailing Mountains, the grade V fuel type areas mainly centralized on Songnen Plain, Sanjiang Plain, and other Plains, and other forest fuel type areas (grades II, III, and IV) were situated between plains and mountainous areas.

Camera calibration and three-dimensional world reconstruction of stereo-vision using neural networks

Stereo-pair images obtained from two cameras can be used to compute three-dimensional (3D) world coordinates of a point using triangulation. However, to apply this method, camera calibration parameters for each camera need to be experimentally obtained. Camera calibration is a rigorous experimental procedure in which typically 12 parameters are to be evaluated for each camera. The general camera model is often such that the system becomes nonlinear and requires good initial estimates to converge to a solution. We propose that, for stereo vision applications in which real-world coordinates are to be evaluated, artificial neural networks be used to train the system such that the need for camera calibration is eliminated. The training set for our neural network consists of a variety of stereo-pair images and corresponding 3D world coordinates. We present the results obtained on our prototype mobile robot that employs two cameras as its sole sensors and navigates through simple regular obstacles in a high-contrast environment. We observe that the percentage errors obtained from our set-up are comparable with those obtained through standard camera calibration techniques and that the system is accurate enough for most machine-vision applications.

Laser Sheet Beam Projector to Recognize the Complex Surfaces of Curvature and Plane.

Using a laser sheet beam projector combined with a CCD-camera, an efficient technique to recognize thecomplex surfaces of curvature and plane has been demonstrated for the purpose of mobile robotnavigation. In this study, detected pixel images of elliptical arc obtained by laser sheet beam have beenconverted into a corresponding circular arc in the real-world coordinates so that the image processing for theposition and radius measurement became more precise and efficient than conventional techniquesbased ondirect elliptical arc analyses. Advantages of this method includes i) higher measurementaccuracy and shorter processing time, and ii) the capability of distinguishing curvature/planecomplexsurfaces. This technique yields an accuracy less than 2 cm for a 28.5 cm radius column at the distance of 70-250 cm from the robot, the obtained accuracy is significantly small enough to navigate a mobile robotoperating in indoor environments.

A New Development in Camera Calibration: Calibrating a Pair of Mobile Cameras

A new method of camera calibration is proposed for active visual sensing for use in three-dimensional (3D) scene analy sis. The method permits calibration of a mobile camera as a function of the position and orientation of the camera. The algorithm for identification of the calibration matrices is divided into two steps: first, calibration for a fixed position of the camera (i.e., the transformation between the real-world coordinates and the coordinates of the corresponding points in the image plane of the camera); second, calibration as a function of the position and orientation of the camera, which uses the prior information of the calibration for a fixed posi tion. The method can be used for any mobile camera as long as the movement of the camera support is known. For instance, if the camera is mounted on the tip of a robot or on a link, we must know the geometric transformation between this link and the base of the robot, but it is not necessary to know the placement of the camera on this link.