Photogrammetric Techniques for Road Surface Analysis

Knyaz, V. A.; Чибуничев, А. Г.

doi:10.5194/isprsarchives-xli-b5-515-2016

Cited by 25 publications

(11 citation statements)

References 2 publications

(2 reference statements)

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“…However, the real demonstration of the integration of these technologies in assessing damages is not discussed. Knyaz and Chibunichev (2016) presented two photogrammetric techniques for road surface analysis (i.e. deformation/unevenness etc.)…”

Section: Highway Infrastructure Managementmentioning

confidence: 99%

Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges

Outay

Mengash

Adnan

2020

Transportation Research Part A: Policy and Practice

190

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For next-generation smart cities, small UAVs (also known as drones) are vital to incorporate in airspace for advancing the transportation systems. This paper presents a review of recent developments in relation to the application of UAVs in three major domains of transportation, namely; road safety, traffic monitoring and highway infrastructure management. Advances in computer vision algorithms to extract key features from UAV acquired videos and images are discussed along with the discussion on improvements made in traffic flow analysis methods, risk assessment and assistance in accident investigation and damage assessments for bridges and pavements. Additionally, barriers associated with the wide-scale deployment of UAVs technology are identified and countermeasures to overcome these barriers are discussed, along with their implications.

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Section: Highway Infrastructure Managementmentioning

confidence: 99%

Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges

Outay

Mengash

Adnan

2020

Transportation Research Part A: Policy and Practice

190

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“…Especially, drone photogrammetry became a popular solution for road damage detection due to their ease of use and versatility. Knyaz et al (2016) applied photogrammetric methods to measure road surface and reconstruct the 3D model for road surface management. Díaz-Vilariño el al (2016) found that photogrammetry using unmanned aerial vehicles (UAVs) could achieve good accuracy and affordable cost for road runoff evaluation.…”

Section: * Corresponding Authormentioning

confidence: 99%

Real-Time Drone Mapping Based on Reference Images for Vehicle Facility Monitoring

Kim

Ham

Lee

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Facilities such as road, parking lots play an important role in our lives nowadays. Damage to such a vehicle facility can cause human injury, as well as inconvenience and cost. To prevent this, facility monitoring is performed periodically, but the current monitoring method is low efficiency by blocking the facility or performing it late at night. In order to increase the efficiency of monitoring, research using images, especially drone images, was conducted. However, when using a drone image, there is a trade-off relationship between accuracy and processing time. In this study, we propose a real-time drone mapping based on reference images for efficient vehicle facility monitoring. The real-time drone mapping based on the reference image is composed of reference images build, aerial triangulation (AT) based on reference images (refAT), and orthophoto generation. The refAT refers to a method of performing AT by using a reference images as reference data. We compared the processing time and processing accuracy of direct georeferencing and refAT. We built 154 drone reference images in the target area. The refAT showed a processing time of about 8.95 seconds and an accuracy of 3.4 cm, and the direct georeferencing method showed a processing time of about 1.49 seconds and an accuracy of 22.5 m. If the method of this study is used for facility monitoring, it is expected that the efficiency of monitoring will be improved with speed and accuracy.

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“…Textured surface 3D models of paleoanthropological objects were obtained using an original photogrammetric system developed in the State Research Institute of Aviation System [Kny16]. For purposes of paleoanthropological analysis 3D models of paleoanthropological objects have to be of high geometric accuracy and of high resolution (detailing).…”

Section: Photogrammetrymentioning

confidence: 99%

Creating digital models of paleoanthrological sample by photogrammetry and computed tomography

Novikov¹,

Knyaz²,

Galeev³

2019

Computer Science Research Notes

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The specificity of paleoanthropological researchs and accurate anthropological documentation is due to the complexity of the form of anthropological objects, their uniqueness, high historical and scientific value. The main purpose of this work is to develop methods for creating 3D models with a high degree of informatively for the development of digital documentation systems of paleoanthropological objects. The article presents a comparative analysis of digital models of anthropological object create using photogrammetry and computed tomography. It is shown that the combined use of non-contact methods of photogrammetry and computed tomography allows to create high-precision three-dimensional models with photorealistic texture and accurate internal and hidden geometry. The proposed approach allows not only to create virtual collections for wide sharing of specialists, but also using modern methods of additive manufacturing to make exact copies of unique artifacts.

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Photogrammetric Techniques for Road Surface Analysis

Cited by 25 publications

References 2 publications

Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges

Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges

Real-Time Drone Mapping Based on Reference Images for Vehicle Facility Monitoring

Creating digital models of paleoanthrological sample by photogrammetry and computed tomography

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