Close Range Photogrammetry: Principles, Methods And Applications

Granshaw, Stuart I.

doi:10.1111/j.1477-9730.2010.00574_1.x

Cited by 14 publications

(8 citation statements)

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“…The close range photogrammetry can be divided into three major processes, including close range photography, image processing and 3D reconstruction [10]. After the image acquisition, a series of processing and operation of the image is needed to complete the three-dimensional reconstruction.…”

Section: Acrp Systemmentioning

confidence: 99%

“…In order to have sufficient overlap between the captured images, the traditional close range photogrammetry needs to capture more than 6 pictures around the object to be measured [9]. The number of image acquisition greatly affects the measurement efficiency, especially the processing time of post-image and operation time of three-dimensional modeling [10]. In order to improve the efficiency of obtaining the surface texture of asphalt pavement by the method of CRP, some scholars use the close range photogrammetry method based on dual camera to collect the surface texture of asphalt mixture specimen [7].…”

Section: Introductionmentioning

confidence: 99%

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Acquisition method of asphalt pavement texture information based on the CPR Technology

et al. 2019

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In order to obtain the asphalt pavement texture information in real time and accurately monitor the anti-skid performance of the road pavement, an automatic close range photogrammetry system (ACPR system) was proposed and built based on the circle arranged three cameras close range photogrammetry (CPR) technology to obtain the asphalt pavement surface texture. Automatic image acquisition and 3D reconstruction were achieved by the ACPR system. Sand patch method and laser scanning method (ZGScan) were used to collect the on-site comparison test of the asphalt pavement texture. Mean texture depth (MTD) and root mean square roughness (RSMR) were chosen as the statistical indicators of road surface texture. The results show that the texture data obtained by ACPR system has relatively high accuracy and efficiency, and the recognition accuracy is close to 0.02mm. The ACPR system improves the efficiency and accuracy of traditional close range photogrammetry and provides real-time and effective road surface anti-skid information for subsequent safety braking of autonomous vehicle.

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Section: Acrp Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Acquisition method of asphalt pavement texture information based on the CPR Technology

et al. 2019

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“…There are guides and documentation available on the best practice for taking photographs to be used in the photogrammetry process [11]. In this section, the main steps of the photogrammetry computer program are introduced, including common issues related to constructing accurate and representative 3D point cloud data in the photography stage.…”

Section: Photogrammetry -Practical Considerationsmentioning

confidence: 99%

“…Minimising shiny surfaces and avoiding specular reflections has the largest effect on the photogrammetry results [11]. Reflections in the surfaces will move relative to the object in each photo.…”

Section: Photogrammetry -Practical Considerationsmentioning

confidence: 99%

Multivariate analysis of curvature estimators

Váša

Kühnert

Brunnett

2016

Computer-Aided Design and Applications

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The photogrammetry procedure is introduced as a cheap and -effective alternative to 3D scanning for constructing 3D point cloud data for reverse engineering applications. The data is then manipulated to generate CAD-ready models for FEA simulations or 3D printing purposes. A practical demonstration using model cars is conducted to show the effectiveness of the procedure in generating point cloud data, and various improvements are introduced. In particular, and innovative to this research work, a feature segmentation algorithm based on color information captured from photographs is implemented. This program, embedded within the photogrammetry process, allows for automatic selection of parts and features from an assembly model, providing a leading advantage over current 3D scanners, which capture spatial data only. Moreover, an intuitive method of enhancing the selection of required features of a triangular mesh during the segmentation process is introduced. This is achieved by manually marking the boundaries on the part of the object to be selected prior to taking photos. This has been proved to be more effective where areas of the object parts have similar colors.

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“…Passive stereo vision 6 composed by two or more cameras can obtain depth information by finding same points in different images. This widely used technique can provide accurate depth estimates on texture objects, but often fails when the surface of the object is low-textured or textureless.…”

Section: Introductionmentioning

confidence: 99%

Design and calibration of a three-dimensional localization system for automatic measurement of long and thin tube based on camera and laser displacement sensor

Zhuang

Gao

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part C:

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An integrated system consisting of robot and laser scanner is considered as a promising alternative measurement device for three-dimensional tube which is long and thin. A key to achieving automatic measurement is to locate tube accurately and robustly, which is precondition for scanning path planning. Thus, a novel three-dimensional localization system consisting of camera and laser displacement senor is proposed. When fixed on robot, the camera can search tube quickly in large view and the laser displacement sensor obtains depth information of key points. Measurement principles are presented firstly, including four main steps: camera shooting, key points extraction, laser displacement sensor shooting, and coordinate calculation. Then, the location error influenced by parameters of camera model and laser displacement sensor is analyzed and illustrated by a specific camera and laser displacement sensor. Furthermore, a scan strategy is proposed for quite thin tube localization. Location error caused by perspective is also analyzed and a compensation method is proposed for decreasing the error. Additionally, a sensor transformation calibration method is presented for identifying the relationship between camera and laser displacement sensor, which is verified with high accuracy by calibration experiments. A contrast experiment of a cylinder bar localization shows that the maximum location error of the camera and laser displacement sensor is no more than 3.5 mm, which is only one-eighth of that of Kinect sensor. The mean and maximum location errors are within 2 mm and 3 mm when locating a car brake and fuel tube with about 1300 mm long, indicating high accuracy and good robustness of designed localization system.

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Close Range Photogrammetry: Principles, Methods And Applications

Cited by 14 publications

References 0 publications

Acquisition method of asphalt pavement texture information based on the CPR Technology

Acquisition method of asphalt pavement texture information based on the CPR Technology

Multivariate analysis of curvature estimators

Design and calibration of a three-dimensional localization system for automatic measurement of long and thin tube based on camera and laser displacement sensor

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