Pan Angles Research Articles

Accuracy Analysis of a Dual Camera System with an Asymmetric Photogrammetric Configuration

AbstractThis paper presents a dual camera system combining a wide field-of-view (FOV) surveillance camera and a pan-tiltzoom (PTZ) camera with an asymmetric photogrammetric configuration, and focuses on the analysis of its attainable measurement accuracy. First, we discuss the geometric modeling of the asymmetric photogrammetric configuration and analyze the accuracy of measurement based on error propagation for different baseline lengths, different focal lengths, and different pan angles of the PTZ camera. Second, we performed a comprehensive accuracy analysis based on Monte Carlo simulation, which incorporated artificial noise into the input data. Third, we conducted actual experiments in indoor and outdoor environments to verify the theoretical and simulation results. We found that the baseline length between the dual cameras was the main factor influencing measurement accuracy. Increase of the PTZ camera focal length could improve the measurement accuracy, but this trend was not significant when its focal length was relatively long. The pan angle of the PTZ camera also influenced the measurement accuracy, but this influence was not significant at short ranges. From these discoveries, we present an optimum configuration of the dual camera system for better than 1 percent measurement accuracy of the range within a normal observation range (e.g., 60 m). This proposed dual camera system provides enhanced machine vision capabilities that can be used in various applications.

Camera Calibration Method Exploiting Reference Images and Roadway Information for Traffic Applications

A video-based traffic flow detection system requires calibration of cameras to generate accurate estimates of vehicle speed. Traditional manual calibration methods cannot satisfy this requirement because calibration has complex procedures. A new traffic camera calibration method is proposed, which exploits reference images and roadway information. The proposed method requires only two parallel lane markings with a known width and a line perpendicular to the lane markings. Camera parameters, including focal length, tilt angle, pan angle, and camera height, can be recovered. A method based on reference images is further proposed to calculate ill-conditioned camera parameters, in which reference images are acquired by a rotating camera while keeping focal length unchanged. Camera recalibration can be easily realized through reference images and roadway information when cameras are moved manually. Simulation experiments demonstrate that the proposed method has the advantages of simple operation and accurate parameter estimations. The method also requires no manual operations and saves manpower.

Investigation of Child Restraint System (CRS) Compatibility in the Vehicle Seat Environment

Objective: Child restraint system (CRS) misuse is common and can have serious consequences to child safety. Physical incompatibilities between CRS and vehicles can complicate the installation process and may worsen CRS misuse rates. This study aims to identify the most common sources of incompatibility between representative groups of CRS and vehicles.Methods: Detailed dimensional data were collected from 59 currently marketed CRS and 61 late model vehicles. Key dimensions were compared across all 3,599 theoretical CRS/vehicle combinations and the most common predicted incompatibilities were determined. A subset of 34 physical installations was analyzed to validate the results.Results: Only 58.2% of rear-facing (RF) CRS/vehicle combinations were predicted to have proper agreement between the vehicle's seat pan angle and the CRS manufacturers’ required base angle. The width of the base of the CRS was predicted to fit snugly between the vehicle's seat pan bolsters in 63.3% of RF CRS/vehicle combinations and 62.2% of forward-facing (FF) CRS/vehicle combinations. FF CRS were predicted to be free of interaction with the vehicle's head restraint in 66.4% of combinations. Roughly 90.0% of RF CRS/vehicle combinations were predicted to have enough horizontal clearance space to set the front seat in the middle its fore/aft slider track. Compatibility rates were above 98% regarding the length of the CRS base compared to the length of the vehicle seat pan and the ability of the top tether to reach the tether anchor. Validation studies revealed that the predictions of RF CRS base angle range vs. seat pan angle compatibility were accurate within 6%, and head restraint interference and front row clearance incompatibilities may be more common than the dimensional analysis approach has predicted.Conclusions: The results of this study indicate that RF CRS base angles and front row clearance space, as well as FF CRS head restraint interference, are frequent compatibility concerns. These results enable manufacturers, researchers, and consumers to focus their attention on the most relevant CRS/vehicle incompatibility issues in today's market.

차선검출 기반 카메라 포즈 추정

Abstract : When a camera installed on a vehicle is used, estimation of the camera pose including tilt, roll, and pan angle with respect to the world coordinate system is important to associate camera coordinates with world coordinates. Previous approaches using huge calibration patterns have the disadvantage that the calibration patterns are costly to make and install. And, previous approaches exploiting multiple vanishing points detected in a single image are not suitable for automotive applications as a scene where multiple vanishing points can be captured by a front camera is hard to find in our daily environment. This paper proposes a camera pose estimation method. It collects multiple images of lane markings while changing the horizontal angle with respect to the markings. One vanishing point, the cross point of the left and right lane marking, is detected in each image, and vanishing line is estimated based on the detected vanishing points. Finally, camera pose is estimated from the vanishing line. The proposed method is based on the fact that planar motion does not change the vanishing line of the plane and the normal vector of the plane can be estimated by the vanishing line. Experiments with large and small tilt and roll angle show that the proposed method outputs accurate estimation results respectively. It is verified by checking the lane markings are up right in the bird’s eye view image when the pan angle is compensated.

App Controllable Intelligent Desk Lamp System

In this paper, we propose a FPGA based intelligent desk lamp system with a camera, two servo motors and LEDs. The proposed lamp system can automatically trace a moving book with a red bookmark by pan and tilt control to provide sufficient illumination. Thus, the user can read book with enough light for eye caring. The architecture of the system includes a vision system and a servo-motor control system. The image processing module inside the system can obtain the book’s position data. According to the book’s position data, two servo motors automatically adjust the pan and tilt angles of the desk lamp. The adjustable ranges for pan and tilt angles are 40° and 30°, respectively. Additionally, an App is designed and allows the user to remotely control the lamp by using a smartphone. All the processing modules are implemented on Altera DE0-Nano kit with Cyclonetex® IV EP4CE22F17C6N FPGA with Verilog HDL.

Camera Control in Multi-Camera Systems for Video Quality Enhancement

Multiview video captured by multi-camera systems has been widely used in many applications such as surveillance, 3D television, and free viewpoint television. After capturing, the multi-camera system generally requires to compress a large amount of multiview data due to limitations on the transmission capacity. To improve video quality, previous work on video compression focused on algorithm refinements when a raw multiview video is compressed at a limited bit-rate, whereas existing work on instrumentation generally introduced higher resolution capture and additional hardware. In contrast, this paper uses camera control to enhance video quality. Individual cameras are controlled to adjust their pan angles and focal lengths to compensate for both object location difference and color inconsistency among camera views at the video acquisition stage. Such a compensation makes the camera images more similar and therefore improves the video quality when a raw multiview video is compressed at a limited bit-rate. The optimal pan angle and focal length are designed for each camera. An example application is to monitor a potted plant in real time for ornamental horticulture study. Experimental results validate the camera control method.

A two-point spatial mapping method for hybrid vision systems

We propose a new spatial mapping method for hybrid vision systems consisting of an omnidirectional camera and an active perspective camera. We calculate the relative position between the optical centers of the two cameras based on pre-acquisition parameters of two sample points from the observed scene, avoiding the difficulty and error in direct measurement, and at the same time using fewer points. We derive the formula of the relative position between the omnidirectional camera’s optical center and the active camera’s optical center from the distance between two points, and give a method for calculating the corresponding pan and tilt angles of the active camera from the coordinates in the omnidirectional image. Simulation and real experiments show that the two-point spatial mapping method has higher estimation accuracy than the homography calibration method, and at the same time has higher consistency among test points.

Detection Of Moving Object Using Foreground Extraction Algorithm By Ptz Camera

This paper proposes a way of recognition foreground of moving object by Foreground Extraction algorithm by Pan-Tilt-Zoom camera. It presents the combined process of Foreground Extraction and local histogram process. Background images are often modeled as multiple frames and their corresponding camera pan and tilt angles are determined. Initially have got to work out the foremost matchedbackground from sequence of input frames based on camera pose information.The method is more continued by compensating the matched background image with this image. Then Background Subtraction is completed between modeled background and current image. Finally before local histogram process is completed, noises are often removed by morphological operators. As a result correct foreground moving objects are successfully extracted by implementing these four steps .

Simple method for camera calibration of roundabout traffic scenes using a single circle

In this study, the authors present a simple method to estimate intrinsic and extrinsic parameters of the camera for roundabout traffic scenes. Unlike many previous works on camera calibration for roadway scenes by using parallel lines, the proposed work addresses camera calibration for roundabout scenes by using a circle. The proposed method can estimate focal length, pan angle, tilt angle and camera height by matching the ellipse equation extracted from an image with the perspective-transformed equation of the corresponding real-world circle. This method requires only one image for camera calibration. The method is validated with real-world roundabout traffic scenes and the calibration results are reasonably accurate compared with ground truth measurements.

Control of Pan-tilt Mechanism Angle using Position Matrix Method

Control of a Pan-Tilt Mechanism (PTM) angle for the bomb disposal robot Morolipi-V2 using inertial sensor measurement unit, x-IMU, has been done. The PTM has to be able to be actively controlled both manually and automatically in order to correct the orientation of the moving Morolipi-V2 platform. The x-IMU detects the platform orientation and sends the result in order to automatically control the PTM. The orientation is calculated using the quaternion combined with Madwick and Mahony f ilter methods. The orientation data that consists of angles of roll ( α ), pitch ( β ), and yaw ( γ ) from the x-IMU are then being sent to the camera for controlling the PTM motion (pan 8 tilt angles) after calculating the reverse angle using position matrix method. Experiment results using Madwick and Mahony methods show that the x-IMU can be used to find the robot platform orientation. Acceleration data from accelerometer and flux from magneto meter produce noise with standard deviation of 0.015 g and 0.006 G, respectively. Maximum ab solute errors caused by Madgwick and Mahony method with respect to X- axis are 48.45º and 33.91º, respectively. The x-IMU im plementation as inertia sensor to control the Pan-Tilt Mechanism shows a good result, which the probability of pan angle tends to be the same with yaw and tilt angle equal to the pitch angle, except a very small angle shift due to the influence of roll angle.

Effect of audio instruction on tracking errors using a four‐dimensional image‐guided radiotherapy system

The Vero4DRT (MHI‐TM2000) is capable of performing X‐ray image‐based tracking (X‐ray Tracking) that directly tracks the target or fiducial markers under continuous kV X‐ray imaging. Previously, we have shown that irregular respiratory patterns increased X‐ray Tracking errors. Thus, we assumed that audio instruction, which generally improves the periodicity of respiration, should reduce tracking errors. The purpose of this study was to assess the effect of audio instruction on X‐ray Tracking errors. Anterior‐posterior abdominal skin‐surface displacements obtained from ten lung cancer patients under free breathing and simple audio instruction were used as an alternative to tumor motion in the superior‐inferior direction. First, a sequential predictive model based on the Levinson‐Durbin algorithm was created to estimate the future three‐dimensional (3D) target position under continuous kV X‐ray imaging while moving a steel ball target of 9.5 mm in diameter. After creating the predictive model, the future 3D target position was sequentially calculated from the current and past 3D target positions based on the predictive model every 70 ms under continuous kV X‐ray imaging. Simultaneously, the system controller of the Vero4DRT calculated the corresponding pan and tilt rotational angles of the gimbaled X‐ray head, which then adjusted its orientation to the target. The calculated and current rotational angles of the gimbaled X‐ray head were recorded every 5 ms. The target position measured by the laser displacement gauge was synchronously recorded every 10 msec. Total tracking system errors (ET) were compared between free breathing and audio instruction. Audio instruction significantly improved breathing regularity (p < 0.01). The mean ± standard deviation of the 95th percentile of ET (E95T) was 1.7 ± 0.5 mm (range: 1.1–2.6 mm) under free breathing (E95T,FB) and 1.9 ± 0.5 mm (range: 1.2–2.7 mm) under audio instruction (E95T,AI). E95T,AI was larger than E95T,FB for five patients; no significant difference was found between E95T,FB and ET,AI95(p = 0.21). Correlation analysis revealed that the rapid respiratory velocity significantly increased E95T. Although audio instruction improved breathing regularity, it also increased the respiratory velocity, which did not necessarily reduce tracking errors.PACS number: 87.55.ne, 87.57.N‐, 87.59.C‐,

가상 시뮬레이션을 이용한 기동형 경계 로봇의 영상 기반 목표추적 알고리즘 검증

In this study, a 3-axis camera system design is proposed for application to an existing 2-axis surveillance robot. A camera-image-based target-tracking algorithm for this robot has also been proposed. The algorithm has been validated using a virtual simulation. In the algorithm, the heading direction vector of the camera system in the mobile surveillance robot is obtained by the position error between the center of the view finder and the center of the object in the camera image. By using the heading direction vector of the camera system, the desired pan and tilt angles for target-tracking and the desired roll angle for the stabilization of the camera image are obtained through inverse kinematics. The algorithm has been validated using a virtual simulation model based on MATLAB and ADAMS by checking the corresponding movement of the robot to the target motion and the virtual image error of the view finder.

Bus surveillance: how many and where cameras should be placed

Public transport safety is an important issue that has recently gained substantial attention, especially with the increasing number of violent incidents occurring abroad. To avoid such incidents and to perform post-incident investigations, many buses today are equipped with surveillance cameras. These cameras are usually installed in key places such as doors, the front and the middle of the bus. This camera placement is often performed manually based on human intuition and knowledge; however, there is no scientific basis to justify: (1) how many cameras would be sufficient, and (2) where (location) and how (with what orientation) they should be placed, to increase the area of coverage at the minimum cost. This paper addresses this issue by breaking it down into two separate problems: MaxGain and MinCost. The MaxGain problem is aimed to maximize the overall coverage with a specific number of cameras; while the MinCost problem attempts to minimize the number of cameras to cover a specified area in the bus. The solutions to these two problems are presented. The proposed method computes the approximate coverage of a camera inside the 3D bus model. Furthermore, in order to improve the efficiency of the solution, an algorithm called "SmartMax" is proposed. The proposed solution advises precise locations and orientations (pan and tilt angles) of required cameras and can be used to validate the current camera installations in various types of public transit buses.

Visual navigation of a mobile robot with laser-based collision avoidance

In this paper, we propose and validate a framework for visual navigation with collision avoidance for a wheeled mobile robot. Visual navigation consists of following a path, represented as an ordered set of key images, which have been acquired by an on-board camera in a teaching phase. While following such a path, the robot is able to avoid obstacles which were not present during teaching, and which are sensed by an on-board range scanner. Our control scheme guarantees that obstacle avoidance and navigation are achieved simultaneously. In fact, in the presence of obstacles, the camera pan angle is actuated to maintain scene visibility while the robot circumnavigates the obstacle. The risk of collision and the eventual avoiding behaviour are determined using a tentacle-based approach. The framework can also deal with unavoidable obstacles, which make the robot decelerate and eventually stop. Simulated and real experiments show that with our method, the vehicle can navigate along a visual path while avoiding collisions.

Camera Calibration Based on Perspective Geometry and Its Application in LDWS

Abstract In this paper, we present a novel algorithm to calibrate cameras for lane departure warning system(LDWS). The algorithm only need a set of parallel lane markings and parallel lines perpendicular to the ground plane to determine the camera parameters such as the roll angle, the tilt angle, the pan angle and the focal length. Then with the camera height, the positions of objects in world space can be easily obtained from the image. We apply the proposed method to our lane departure warning system which monitors the distance between the car and road boundaries. Experiments show that the proposed method is easy to operate, and can achieve accurate results.

G150042 作業用双腕を有するクローラ型不整地移動ロボットの開発

The Authors have developed a tracked mobile robot that consists of two tracks and two arms. Two tracks surround the robot body. Two 4-DOF arms are attached to left and right front corner of the robot body. One arm has a 1-DOF hand at the end for manipulating an object. Another has a rubber at the end. The robot is therefore able to handle and carry objects on the way when it is moving. A Pan-Tilt CCD camera which can control pan and tilt angles is mounted on the robot with an image processing board in order to detect target objects. This paper describes mechanisms and control system of the robot.

Two‐dimensional standoff Raman measurements of distant samples

AbstractA scanning standoff Raman spectroscopy system has been developed to measure the molecular species of distant samples in two dimensions. Computer software is used to control the scanner pan and tilt angles, and Raman measurements are collected of the distant sample area in an x–y grid pattern. The Raman spectra at each grid point are measured and processed to obtain an image of the distant surface composition. The ability to provide interpolated images of distant molecular species is illustrated. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Dosimetric characterization of a multileaf collimator for a new four‐dimensional image‐guided radiotherapy system with a gimbaled x‐ray head, MHI‐TM2000a)

To present the dosimetric characterization of a multileaf collimator (MLC) for a new four-dimensional image-guided radiotherapy system with a gimbaled x-ray head, MHI-TM2000. MHI-TM2000 has an x-ray head composed of an ultrasmall linear accelerator guide and a system-specific MLC. The x-ray head can rotate along the two orthogonal gimbals (pan and tilt rotations) up to +/- 2.5 degrees, which swings the beam up to +/- 41.9 mm in each direction from the isocenter on the isocenter plane perpendicular to the beam. The MLC design is a single-focus type, has 30 pairs of 5 mm thick leaves at the isocenter, and produces a maximum field size of 150 x 150 mm2. Leaf height and length are 110 and 260 mm, respectively. Each leaf end is circular, with a radius of curvature of 370 mm. The distance that each leaf passes over the isocenter is 77.5 mm. Radiation leakage between adjacent leaves is minimized by an interlocking tongue-and-groove (T&G) arrangement with the height of the groove part 55 mm. The dosimetric characterizations including field characteristics, leaf position accuracy, leakage, and T&G effect were evaluated using a well-commissioned 6 MV photon beam, EDR2 films (Kodak, Rochester, NY), and water-equivalent phantoms. Furthermore, the field characteristics and leaf position accuracy were evaluated under conditions of pan or tilt rotation. The differences between nominal and measured field sizes were within +/- 0.5 mm. Although the penumbra widths were greater with wider field size, the maximum width was < 5.5 mm even for the fully opened field. Compared to the results of field characteristics without pan or tilt rotation, the variation in field size, penumbra width, flatness, and symmetry was within +/- 1 mm/l% at the maximum pan or tilt rotational angle. The leaf position accuracy was 0.0 +/- 0.1 mm, ranging from -0.3 to 0.2 mm at four gantry angles of 0 degrees, 90 degrees, 180 degrees, and 270 degrees with and without pan or tilt rotation. The interleaf leakage was up to 0.21%, whereas the intraleaf leakage was < 0.12%. T&G decreased the doses by 10.7%, on average. This study demonstrated that MHI-TM2000 has the capability for high leaf position accuracy and low leakage, leading to highly accurate intensity-modulated radiotherapy delivery. Furthermore, substantial changes in the dosimetric data on field characteristics and leaf position accuracy were not observed even at the maximum pan or tilt rotation.

CCTV 카메라 시스템에 의한 ARPA 레이더 추적선박의 자동식별

This paper describes a automatic video surveillance system(AVSS) with long range and 360 coverage that is automatically rotated in an elevation over azimuth mode in response to the TTM(tracked target message) signal of vessels tracked by ARPA(automatic radar plotting aids) radar. This AVSS that is a video security and tracking system supported by ARPA radar, CCTV(closed-circuit television) camera system and other sensors to automatically identify and track, detect the potential dangerous situations such as collision accidents at sea and berthing/deberthing accidents in harbor, can be used in monitoring the illegal fishing vessels in inshore and offshore fishing ground, and in more improving the security and safety of domestic fishing vessels in EEZ(exclusive economic zone) area. The movement of the target vessel chosen by the ARPA radar operator in the AVSS can be automatically tracked by a CCTV camera system interfaced to the ECDIS(electronic chart display and information system) with the special functions such as graphic presentation of CCTV image, camera position, camera azimuth and angle of view on the ENC, automatic and manual controls of pan and tilt angles for CCTV system, and the capability that can replay and record continuously all information of a selected target. The test results showed that the AVSS developed experimentally in this study can be used as an extra navigation aid for the operator on the bridge under the confusing traffic situations, to improve the detection efficiency of small targets in sea clutter, to enhance greatly an operator s ability to identify visually vessels tracked by ARPA radar and to provide a recorded history for reference or evidentiary purposes in EEZ area.

Boosting feature selection for Neural Network based regression

The head pose estimation problem is well known to be a challenging task in computer vision and is a useful tool for several applications involving human-computer interaction. This problem can be stated as a regression one where the input is an image and the output is pan and tilt angles. Finding the optimal regression is a hard problem because of the high dimensionality of the input (number of image pixels) and the large variety of morphologies and illumination. We propose a new method combining a boosting strategy for feature selection and a neural network for the regression. Potential features are a very large set of Haar-like wavelets which are well known to be adapted to face image processing. To achieve the feature selection, a new Fuzzy Functional Criterion (FFC) is introduced which is able to evaluate the link between a feature and the output without any estimation of the joint probability density function as in the Mutual Information. The boosting strategy uses this criterion at each step: features are evaluated by the FFC using weights on examples computed from the error produced by the neural network trained at the previous step. Tests are carried out on the commonly used Pointing 04 database and compared with three state-of-the-art methods. We also evaluate the accuracy of the estimation on FacePix, a database with a high angular resolution. Our method is compared positively to a Convolutional Neural Network, which is well known to incorporate feature extraction in its first layers.