Underwater Laser-based Structured Light System for one-shot 3D reconstruction

Massot-Campos, Miquel; Oliver-Codina, Gabriel

doi:10.1109/icsens.2014.6985208

Cited by 38 publications

(21 citation statements)

References 7 publications

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“…Massot and Oliver [ 95 , 96 , 97 ], designed a laser-based structured light system that enhances simpler laser stripe approaches by using a diffractive optical element (DOE) to enhance a simple laser pointer, shaping the beam into 25 parallel lines, called a laser-based structured light (LbSL) system. The pattern is projected on the environment and recovered by a color camera.…”

Section: Sensors and Technologiesmentioning

confidence: 99%

Optical Sensors and Methods for Underwater 3D Reconstruction

Massot-Campos

Oliver-Codina

2015

Sensors

Self Cite

133

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This paper presents a survey on optical sensors and methods for 3D reconstruction in underwater environments. The techniques to obtain range data have been listed and explained, together with the different sensor hardware that makes them possible. The literature has been reviewed, and a classification has been proposed for the existing solutions. New developments, commercial solutions and previous reviews in this topic have also been gathered and considered.

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Section: Sensors and Technologiesmentioning

confidence: 99%

Optical Sensors and Methods for Underwater 3D Reconstruction

Massot-Campos

Oliver-Codina

2015

Sensors

Self Cite

133

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“…This enables the system to produced colored scans by evaluating the intensity of the responses of the different laser projectors. Alternatively, diffractive optical elements are used to project multiple lines or a grid for one shot 3D reconstruction (Morinaga et al, 2016, Massot-Campos, Oliver-Codina, 2014. Calibration of these systems is typically achieved using chessboard patterns or 3D calibration fixtures.…”

Section: Related Workmentioning

confidence: 99%

Scout3d – An Underwater Laser Scanning System for Mobile Mapping

Bleier¹,

Lucht²,

Nüchter³

2019

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

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Abstract. This paper presents an underwater laser scanning system and GNSS based trajectory estimation system for scanning from a surface vessle in shallow water. The system has an above-the-water and an underwater component. Above-the-water two low-cost multiband GNSS receivers with an antenna baseline of one meter are used for RTK positioning with heading. The full 6-DOF is estimated by fusing the satellite navigation data with a MEMS-based INS. The 3D data is captured in water using a structured light scanner consisting of a low-light underwater camera and a green cross line laser projector. We describe the development of the system and employed hardware components. We show results of scanning a large test object in a water tank acquired by from a tripod with a motorized yaw axis. Additionally, we demonstrate first results of mobile mapping from a floating platform. We evaluate the performance of the system by measuring the 6-DOF trajectory with an external optical tracking system. Additionally, we assess the quality of the created point cloud using reference objects placed in the scene.

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“…For weak scattering media, Bleier and Nüchter used cross laser projector which only achieved sparse reconstruction [4]. To increase density, Campos and Codina projected parallel lines with DOE to capture underwater objects with one-shot scan [23]. Kawasaki et al proposed a grid pattern to capture more dense shape with one-shot scan [16].…”

Section: Related Workmentioning

confidence: 99%

CNN Based Dense Underwater 3D Scene Reconstruction by Transfer Learning Using Bubble Database

Ichimaru

Furukawa

Kawasaki³

2019

2019 IEEE Winter Conference on Applications of Computer Vision (WACV)

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Dense 3D shape acquisition of swimming human or live fish is an important research topic for sports, biological science and so on. For this purpose, active stereo sensor is usually used in the air, however it cannot be applied to the underwater environment because of refraction, strong light attenuation and severe interference of bubbles. Passive stereo is a simple solution for capturing dynamic scenes at underwater environment, however the shape with textureless surfaces or irregular reflections cannot be recovered. Recently, the stereo camera pair with a pattern projector for adding artificial textures on the objects is proposed. However, to use the system for underwater environment, several problems should be compensated, i.e., disturbance by fluctuation and bubbles. Simple solution is to use convolutional neural network for stereo to cancel the effects of bubbles and/or water fluctuation. Since it is not easy to train CNN with small size of database with large variation, we develop a special bubble generation device to efficiently create real bubble database of multiple size and density. In addition, we propose a transfer learning technique for multi-scale CNN to effectively remove bubbles and projected-patterns on the object. Further, we develop a real system and actually captured live swimming human, which has not been done before. Experiments are conducted to show the effectiveness of our method compared with the state of the art techniques.

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Underwater Laser-based Structured Light System for one-shot 3D reconstruction

Cited by 38 publications

References 7 publications

Optical Sensors and Methods for Underwater 3D Reconstruction

Optical Sensors and Methods for Underwater 3D Reconstruction

Scout3d – An Underwater Laser Scanning System for Mobile Mapping

CNN Based Dense Underwater 3D Scene Reconstruction by Transfer Learning Using Bubble Database

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