3D Reconstruction of Oil Refinery Buildings Using a Depth Camera

In order to optimize the three-dimensional (3D) reconstruction and obtain more precise actual distances of the object, a 3D reconstruction system combining binocular and depth cameras is proposed in this paper. The whole system consists of two identical color cameras, a TOF depth camera, an image processing host, a mobile robot control host, and a mobile robot. Because of structural constraints, the resolution of TOF depth camera is very low, which difficultly meets the requirement of trajectory planning. The resolution of binocular stereo cameras can be very high, but the effect of stereo matching is not ideal for low-texture scenes. Hence binocular stereo cameras also difficultly meet the requirements of high accuracy. In this paper, the proposed system integrates depth camera and stereo matching to improve the precision of the 3D reconstruction. Moreover, a double threads processing method is applied to improve the efficiency of the system. The experimental results show that the system can effectively improve the accuracy of 3D reconstruction, identify the distance from the camera accurately, and achieve the strategy of trajectory planning.

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Matching-based depth camera and mirrors for 3D reconstruction

Three-Dimensional Imaging, Visualization, and Display 2018 ◽

10.1117/12.2304427 ◽

2018 ◽

Cited By ~ 1

Author(s):

Huu Hung Huynh ◽

Trong Nguyen Nguyen ◽

Jean Meunier

Keyword(s):

3D Reconstruction ◽

Depth Camera

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Fast, Accurate, and Automated 3D Reconstruction Using a Depth Camera Mounted on an Industrial Robot

10.1115/detc2021-71725 ◽

2021 ◽

Author(s):

Rishi Malhan ◽

Rex Jomy Joseph ◽

Prahar M. Bhatt ◽

Brual Shah ◽

Satyandra K. Gupta

Keyword(s):

3D Reconstruction ◽

Cycle Time ◽

Industrial Robot ◽

Low Cost ◽

Point Clouds ◽

Industrial Robots ◽

Depth Camera ◽

Reconstruction Process ◽

Depth Cameras ◽

Manufacturing Applications

Abstract 3D reconstruction technology is used in a wide variety of applications. Currently, automatically creating accurate pointclouds for large parts requires expensive hardware. We are interested in using low-cost depth cameras mounted on commonly available industrial robots to create accurate pointclouds for large parts automatically. Manufacturing applications require fast cycle times. Therefore, we are interested in speeding up the 3D reconstruction process. We present algorithmic advances in 3D reconstruction that achieve a sub-millimeter accuracy using a low-cost depth camera. Our system can be used to determine a pointcloud model of large and complex parts. Advances in camera calibration, cycle time reduction for pointcloud capturing, and uncertainty estimation are made in this work. We continuously capture point-clouds at an optimal camera location with respect to part distance during robot motion execution. The redundancy in pointclouds achieved by the moving camera significantly reduces errors in measurements without increasing cycle time. Our system produces sub-millimeter accuracy.

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3D Reconstruction With Time-of-Flight Depth Camera and Multiple Mirrors

IEEE Access ◽

10.1109/access.2018.2854262 ◽

2018 ◽

Vol 6 ◽

pp. 38106-38114 ◽

Cited By ~ 8

Author(s):

Trong-Nguyen Nguyen ◽

Huu-Hung Huynh ◽

Jean Meunier

Keyword(s):

3D Reconstruction ◽

Time Of Flight ◽

Depth Camera

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Variational Level Set Evolution for Non-rigid 3D Reconstruction from a Single Depth Camera

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2020.2976065 ◽

2020 ◽

pp. 1-1 ◽

Cited By ~ 1

Author(s):

Miroslava Slavcheva ◽

Maximilian Baust ◽

Slobodan Ilic

Keyword(s):

3D Reconstruction ◽

Level Set ◽

Depth Camera ◽

Variational Level Set ◽

Level Set Evolution

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Development of a Wide Area 3D Scanning System with a Rotating Line Laser

Sensors ◽

10.3390/s21113885 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3885

Author(s):

Jaeho Lee ◽

Hyunsoo Shin ◽

Sungon Lee

Keyword(s):

3D Reconstruction ◽

Rotation Axis ◽

Calibration Method ◽

3D Scanning ◽

Wide Area ◽

Limited Area ◽

Scanning System ◽

Depth Camera ◽

Large Area ◽

Geometrical Relationship

In a 3D scanning system, using a camera and a line laser, it is critical to obtain the exact geometrical relationship between the camera and laser for precise 3D reconstruction. With existing depth cameras, it is difficult to scan a large object or multiple objects in a wide area because only a limited area can be scanned at a time. We developed a 3D scanning system with a rotating line laser and wide-angle camera for large-area reconstruction. To obtain 3D information of an object using a rotating line laser, we must be aware of the plane of the line laser with respect to the camera coordinates at every rotating angle. This is done by estimating the rotation axis during calibration and then by rotating the laser at a predefined angle. Therefore, accurate calibration is crucial for 3D reconstruction. In this study, we propose a calibration method to estimate the geometrical relationship between the rotation axis of the line laser and the camera. Using the proposed method, we could accurately estimate the center of a cone or cylinder shape generated while the line laser was rotating. A simulation study was conducted to evaluate the accuracy of the calibration. In the experiment, we compared the results of the 3D reconstruction using our system and a commercial depth camera. The results show that the precision of our system is approximately 65% higher for plane reconstruction, and the scanning quality is also much better than that of the depth camera.

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ALGORITHMS FOR IMPROVING SPEED AND ACCURACY OF AUTOMATED 3D RECONSTRUCTION WITH A DEPTH CAMERA MOUNTED ON AN INDUSTRIAL ROBOT

Journal of Computing and Information Science in Engineering ◽

10.1115/1.4053272 ◽

2021 ◽

pp. 1-13

Author(s):

Rishi K. Malhan ◽

Rex Jomy Joseph ◽

Prahar Bhatt ◽

Brual Shah ◽

Satyandra K. Gupta

Keyword(s):

3D Reconstruction ◽

Cycle Time ◽

Industrial Robot ◽

Low Cost ◽

Industrial Robots ◽

Depth Camera ◽

Reconstruction Process ◽

Depth Cameras ◽

Camera Location ◽

Manufacturing Applications

Abstract 3D reconstruction technology is used in a wide variety of applications. Currently, automatically creating accurate pointclouds for large parts requires expensive hardware. We are interested in using low-cost depth cameras mounted on commonly available industrial robots to create accurate pointclouds for large parts automatically. Manufacturing applications require fast cycle times. Therefore, we are interested in speeding up the 3D reconstruction process. We present algorithmic advances in 3D reconstruction that achieve a sub-millimeter accuracy using a low-cost depth camera. Our system can be used to determine a pointcloud model of large and complex parts. Advances in camera calibration, cycle time reduction for pointcloud capturing, and uncertainty estimation are made in this work. We continuously capture pointclouds at an optimal camera location with respect to part distance during robot motion execution. The redundancy in pointclouds achieved by the moving camera significantly reduces errors in measurements without increasing cycle time. Our system produces sub-millimeter accuracy.

Download Full-text