Camera Calibration for Underwater 3D Reconstruction Based on Ray Tracing Using Snell’s Law

Pedersen, Malte; Bengtson, Stefan Hein; Gade, Rikke; Madsen, Niels; Moeslund, Thomas B.

doi:10.1109/cvprw.2018.00190

Cited by 46 publications

(58 citation statements)

References 21 publications

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“…are obtained by a ray tracing process (Yamashita, Fujii & Kaneko 2008;Pedersen et al 2018) which is described in detail in appendix A.…”

Section: Particle Trackingmentioning

confidence: 99%

“…Since the particle is immersed in oil, the cameras are placed in air, and both fluids are separated by a thick Plexiglas lid, the refraction of the optical ray due to the different indices of refraction needs to be taken into account for the air-Plexiglas and Plexiglas-oil interfaces. Therefore, the position of the particle centroid is determined by ray tracing based on Snell's law (Yamashita et al 2008;Pedersen et al 2018). For each camera, the refracted optical ray from the object point P to the camera-plane centre point C (i) intersects with the air-Plexiglas and Plexiglas-oil interfaces at points P (i) 1 and P (i) 2 , respectively.…”

Section: Declaration Of Interestsmentioning

confidence: 99%

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Attractors for the motion of a finite-size particle in a two-sided lid-driven cavity

Romanò

Kuhlmann

2020

J. Fluid Mech.

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“…are obtained by a ray tracing process (Yamashita, Fujii & Kaneko 2008;Pedersen et al 2018) which is described in detail in appendix A.…”

Section: Particle Trackingmentioning

confidence: 99%

Section: Declaration Of Interestsmentioning

confidence: 99%

Attractors for the motion of a finite-size particle in a two-sided lid-driven cavity

Romanò

Kuhlmann

2020

J. Fluid Mech.

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“…Camera calibration is one of the quintessential issues in computer vision and photogrammetry and has received considerable attention over the last number of years. A variety of calibration techniques, [ 124 , 125 , 126 , 133 , 139 , 140 , 141 , 142 ] to cite a few, have been developed to accommodate various applications, such as AVs, Unmanned Surface Vehicle (USV) or underwater 3D reconstructions. Reference [ 141 ] classified these techniques into: Photogrammetric calibration.…”

Section: Sensor Calibration and Sensor Fusion For Object Detectionmentioning

confidence: 99%

Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

Yeong

Velasco-Hernandez

Barry

et al. 2021

Sensors

441

133

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With the significant advancement of sensor and communication technology and the reliable application of obstacle detection techniques and algorithms, automated driving is becoming a pivotal technology that can revolutionize the future of transportation and mobility. Sensors are fundamental to the perception of vehicle surroundings in an automated driving system, and the use and performance of multiple integrated sensors can directly determine the safety and feasibility of automated driving vehicles. Sensor calibration is the foundation block of any autonomous system and its constituent sensors and must be performed correctly before sensor fusion and obstacle detection processes may be implemented. This paper evaluates the capabilities and the technical performance of sensors which are commonly employed in autonomous vehicles, primarily focusing on a large selection of vision cameras, LiDAR sensors, and radar sensors and the various conditions in which such sensors may operate in practice. We present an overview of the three primary categories of sensor calibration and review existing open-source calibration packages for multi-sensor calibration and their compatibility with numerous commercial sensors. We also summarize the three main approaches to sensor fusion and review current state-of-the-art multi-sensor fusion techniques and algorithms for object detection in autonomous driving applications. The current paper, therefore, provides an end-to-end review of the hardware and software methods required for sensor fusion object detection. We conclude by highlighting some of the challenges in the sensor fusion field and propose possible future research directions for automated driving systems.

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“…Three ways for 3D reconstruction has been evaluated for the task of estimating the 3D position of underwater objects (Pedersen et al, 2018). The compared approaches were: an approach relying solely on in-air camera calibration, an approach with the camera calibration performed under water and an approach based on ray tracing with Snell's law.…”

Section: Related Workmentioning

confidence: 99%

Optical 3d Measurements in Hydrodynamic Tunnel for Aircraft Icing Study

Knyaz

Stepaniants

Ippolitov

et al. 2020

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

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Abstract. The study of how aircraft icing influences on aircraft aerodynamic performance is very important for developing measures and recommendation to improve aircraft flight safety. The effective method of aerodynamic processes modeling is experiment in wind (aerodynamic) tunnel or water (hydrodynamic) tunnel. They allow to perform experiments with a scaled model of an aircraft affected by icing and to visualize the wing flow process and changes caused by icing. While visualization of the wing flow yields useful qualitative information about flow, it is more important to retrieve quantitative 3D data of flow, which allows to forecast icing process and to develop anti-icing techniques and recommendations.The presented study addresses to creating an photogrammetric system and 3D measurement techniques for quantitate evaluation of 3D flow parameters in a hydrodynamic tunnel for aircraft icing influence exploration. Being an initial part of a long-term research project, this study is aimed at developing of an accurate calibration technique of the photogrammetric system for 3D measurement in condition of two optical media interfaces. The developed algorithms for imaging process through two optical media interfaces are used in calibration procedure and object 3D coordinates measuring. The results of the photogrammetric system calibration are given in comparison with standard (single media) case. Experimental 3D reconstruction of a typical object demonstrated high accuracy of the developed algorithms.

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Camera Calibration for Underwater 3D Reconstruction Based on Ray Tracing Using Snell’s Law

Cited by 46 publications

References 21 publications

Attractors for the motion of a finite-size particle in a two-sided lid-driven cavity

Attractors for the motion of a finite-size particle in a two-sided lid-driven cavity

Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

Optical 3d Measurements in Hydrodynamic Tunnel for Aircraft Icing Study

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