Everton Trento Jr., G. Pires, G. A. Guarneri, T. Passarin, D. Pipa
{"title":"浸入式无损检测中深度相机光学畸变校正的数据驱动方法","authors":"Everton Trento Jr., G. Pires, G. A. Guarneri, T. Passarin, D. Pipa","doi":"10.58286/28116","DOIUrl":null,"url":null,"abstract":"\nStereoscopic cameras, also known as depth cameras, are increasingly present in robotics\n\nnavigation and 3D scene reconstruction. Normally, off-the-shelf depth cameras are not\n\nsuited for underwater environments and exhibit considerable distortions in the provided 3D images when operating underwater. This is mainly due to the large difference\n\nin the refractive coefficients of air and water. This issue prevents their use in subsea\n\napplications such as the inspection of oil pipelines, valves and manifolds, where these\n\ndevices could be used for odometry during ultrasonic inspections as well as for 3D scanning. Aiming to allow for such applications, we present a data-driven method for the\n\ncorrection of distortions caused by unaccounted diffractions in depth cameras. First,\n\nthe distortion is modelled via a series of detections of control points from a standard\n\ntarget at known underwater positions, and an approximation of the inverse distortion\n\nis obtained. Then, at runtime, a procedure takes as input the (distorted) point cloud\n\ngiven by the camera at each frame, applies the inverse distortion, and yields a corrected\n\npoint cloud. We apply the method to data provided by a RealSense D405 camera encased in a sealed acrylic container underwater. The correction makes it possible to use\n\nthe camera for odometry underwater, clearing the path for the use of off-the-shelf depth\n\ncameras in a wide range of subsea applications. The method can be applied for any\n\nother transparent fluid.\n\n\n","PeriodicalId":383798,"journal":{"name":"Research and Review Journal of Nondestructive Testing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A data-driven method for the correction of optical distortions of depth cameras in immersion NDT\",\"authors\":\"Everton Trento Jr., G. Pires, G. A. Guarneri, T. Passarin, D. Pipa\",\"doi\":\"10.58286/28116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nStereoscopic cameras, also known as depth cameras, are increasingly present in robotics\\n\\nnavigation and 3D scene reconstruction. Normally, off-the-shelf depth cameras are not\\n\\nsuited for underwater environments and exhibit considerable distortions in the provided 3D images when operating underwater. This is mainly due to the large difference\\n\\nin the refractive coefficients of air and water. This issue prevents their use in subsea\\n\\napplications such as the inspection of oil pipelines, valves and manifolds, where these\\n\\ndevices could be used for odometry during ultrasonic inspections as well as for 3D scanning. Aiming to allow for such applications, we present a data-driven method for the\\n\\ncorrection of distortions caused by unaccounted diffractions in depth cameras. First,\\n\\nthe distortion is modelled via a series of detections of control points from a standard\\n\\ntarget at known underwater positions, and an approximation of the inverse distortion\\n\\nis obtained. Then, at runtime, a procedure takes as input the (distorted) point cloud\\n\\ngiven by the camera at each frame, applies the inverse distortion, and yields a corrected\\n\\npoint cloud. We apply the method to data provided by a RealSense D405 camera encased in a sealed acrylic container underwater. The correction makes it possible to use\\n\\nthe camera for odometry underwater, clearing the path for the use of off-the-shelf depth\\n\\ncameras in a wide range of subsea applications. The method can be applied for any\\n\\nother transparent fluid.\\n\\n\\n\",\"PeriodicalId\":383798,\"journal\":{\"name\":\"Research and Review Journal of Nondestructive Testing\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research and Review Journal of Nondestructive Testing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.58286/28116\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research and Review Journal of Nondestructive Testing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58286/28116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A data-driven method for the correction of optical distortions of depth cameras in immersion NDT
Stereoscopic cameras, also known as depth cameras, are increasingly present in robotics
navigation and 3D scene reconstruction. Normally, off-the-shelf depth cameras are not
suited for underwater environments and exhibit considerable distortions in the provided 3D images when operating underwater. This is mainly due to the large difference
in the refractive coefficients of air and water. This issue prevents their use in subsea
applications such as the inspection of oil pipelines, valves and manifolds, where these
devices could be used for odometry during ultrasonic inspections as well as for 3D scanning. Aiming to allow for such applications, we present a data-driven method for the
correction of distortions caused by unaccounted diffractions in depth cameras. First,
the distortion is modelled via a series of detections of control points from a standard
target at known underwater positions, and an approximation of the inverse distortion
is obtained. Then, at runtime, a procedure takes as input the (distorted) point cloud
given by the camera at each frame, applies the inverse distortion, and yields a corrected
point cloud. We apply the method to data provided by a RealSense D405 camera encased in a sealed acrylic container underwater. The correction makes it possible to use
the camera for odometry underwater, clearing the path for the use of off-the-shelf depth
cameras in a wide range of subsea applications. The method can be applied for any
other transparent fluid.