DSpace Collection:
http://hdl.handle.net/2115/54832
Sat, 12 Jun 2021 22:49:30 GMT2021-06-12T22:49:30Z深層学習を用いた回転機のトポロジー最適化に関する研究 [論文内容及び審査の要旨]
http://hdl.handle.net/2115/81714
Title: 深層学習を用いた回転機のトポロジー最適化に関する研究 [論文内容及び審査の要旨]
Authors: 佐々木, 秀徳Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/817142021-03-24T15:00:00Z佐々木, 秀徳深層学習を用いた回転機のトポロジー最適化に関する研究 [全文の要約]
http://hdl.handle.net/2115/81681
Title: 深層学習を用いた回転機のトポロジー最適化に関する研究 [全文の要約]
Authors: 佐々木, 秀徳
Description: この博士論文全文の閲覧方法については、以下のサイトをご参照ください。Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/816812021-03-24T15:00:00Z佐々木, 秀徳Study on model order reduction for Maxwell's equations based on Krylov subspace methods [an abstract of entire text]
http://hdl.handle.net/2115/81669
Title: Study on model order reduction for Maxwell's equations based on Krylov subspace methods [an abstract of entire text]
Authors: 比留間, 真悟
Description: この博士論文全文の閲覧方法については、以下のサイトをご参照ください。Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/816692021-03-24T15:00:00Z比留間, 真悟Study on model order reduction for Maxwell's equations based on Krylov subspace methods [an abstract of dissertation and a summary of dissertation review]
http://hdl.handle.net/2115/81667
Title: Study on model order reduction for Maxwell's equations based on Krylov subspace methods [an abstract of dissertation and a summary of dissertation review]
Authors: 比留間, 真悟Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/816672021-03-24T15:00:00Z比留間, 真悟Multiple Paired Pixel Consistency Model for Robust Defect Detection in Printed Logotypes
http://hdl.handle.net/2115/81623
Title: Multiple Paired Pixel Consistency Model for Robust Defect Detection in Printed Logotypes
Authors: Xiang, Sheng
Abstract: In modern manufacturing, quality control (QC) is an integral technique. Detection of product flaws plays a crucial role in quality management and ensuring that the product serves the consumer. In this study, we assess how currently available vision systems execute a range of QC tasks on printed items. In particular, we take into consideration the examination of printed characters/text or logotypes for defects, such as holes, scratches,cracks, and foreign artifacts. Printing-defect analysis is currently most done by human testers, and is labor-intensive and time-consuming job. Moreover, the results of an inspection might be unreliable because humans may arrive at different results depending on the time and the mood, skills, and experience of the inspectors. Therefore, human inspection is being replaced by automatic visual inspection systems.
Traditional defect-detection algorithms can be categorized as conventional feature-based and data-driven-based algorithms. Furthermore, conventional feature-based methods can be divided into four categories: statistical-, structure-, filter-, and model-based methods. Data-driven-based methods can be divided into two categories: traditional machine learning methods and deep learning techniques. Both data-driven-based and feature-based algorithms have their advantages and disadvantages. Feature-based methods usually have clear algorithmic implications and are therefore easy to control. Suitable features for various application scenarios can be configured for specific objectives. In comparison, feature-based methods are typically effective and simple to implement since they do not rely on massive quantities of data. However, certain difficulties do occur, such as the failure inability to detect small-sized defects and texture irregularities satisfactorily. Data-driven methods are usually implemented by designing certain learnable parameters of the model and then teaching the data model. Training data usually contains images and corresponding annotations that are manually annotated. While data-driven methods exhibit high precision and generalization, they involve a significant amount of learned data and manual annotations. The training phase often involves substantial computational capital and time.
This work focuses on the identification of printing defects on surfaces embossed using randomly spaced three-dimensional (3D) micro-textures. The embossing processes ∗Doctoral Thesis, Division of Systems Science and Informatics, Graduate School of Information Science and Technology, Hokkaido University, SSI-DT79185030, January 6, 2021. produces a very small variety of convex and concave shapes on the surfaces of metals, plastics, or other materials. Changes in the illumination on certain surfaces have a major effect on their appearance, resulting in difficulty in identifying defects. To realize this goal, the use of the multiple paired pixel consistency (MMPC) model was recommended. We first propose a consistency measure based on the correlation of consistent pixel pairs to obtain a robust defect-free model. We then set in motion a new assessment technique to accurately identify defects. Furthermore, a modification method called position-dependent data inhibition (PDI) is proposed to further improve the robustness and performance of the MPPC model.
This overall dissertation is structured as follows.
Chapter 1 introduces the importance of identification of defects and presents the associated works on defect detection. Some challenges in defect detection are discussed. Furthermore, the motivations and contributions of this study are explained.
Chapter 2 introduces the orientation codes (OCs), the use of which could reduce the influence of illumination fluctuations on defect detection; thus, OCs are used as the basis of the proposed method. First, we implement the original version of the OCs and then expand it by presenting two types of operations: a precise spatial differentiation for calculating the codes with a higher resolution and signed difference between any two codes as preparation for building up a more precise statistical model of their difference. Using these operations, we add a more reliable scheme to explain the statistical relationship between a pair of any logotypes pixels.
Chapter 3 introduces the proposed MPPC model in detail, including the fundamental principle and structure of the MPPC model. First, we observe the defect-free images of logotypes to determine the relationship between any pair of pixels in the logotype. We then introduce kurtosis to obtain the potential distributions. After analyzing the distributions, we explain how to pick the supporting pixel for each target pixel and finally construct the MPPC model for each pixel pair.
Chapter 4 provides a discussion of the method for using the proposed MPPC model of the relationship between pixel pairs in the defect-free logotype for identification of several types of logotype defects. Defect detection can be divided into two main stages. First, the status of each pixel pair is determined. We then identify the normal or abnormal states at the corresponding position defined by the elemental MPPC model.
Chapter 5 is focused on the PDI modification suggested on the basis of MPPC to further strengthen the robustness of the MPPC and stabilize its performance. The basic principles and mechanism of the PDI are explored in depth in this chapter. Finally, we verify the capacity of the PDI by appropriate experiments.
Chapter 6 lays out the experimental setup in detail. In this chapter, comparative experiments for the MPPC and MPPC+PDI models using several real defective images and synthesized or artificial defective images under different conditions such as illumination fluctuation and different noise intensities are designed. We test the robustness and efficiency of our methods through these experiments.
The final chapter outlines the key points of this study and presents a discussion of our algorithms. Finally, the strategy and idea for possible future works are discussed.Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/816232021-03-24T15:00:00ZXiang, ShengIn modern manufacturing, quality control (QC) is an integral technique. Detection of product flaws plays a crucial role in quality management and ensuring that the product serves the consumer. In this study, we assess how currently available vision systems execute a range of QC tasks on printed items. In particular, we take into consideration the examination of printed characters/text or logotypes for defects, such as holes, scratches,cracks, and foreign artifacts. Printing-defect analysis is currently most done by human testers, and is labor-intensive and time-consuming job. Moreover, the results of an inspection might be unreliable because humans may arrive at different results depending on the time and the mood, skills, and experience of the inspectors. Therefore, human inspection is being replaced by automatic visual inspection systems.
Traditional defect-detection algorithms can be categorized as conventional feature-based and data-driven-based algorithms. Furthermore, conventional feature-based methods can be divided into four categories: statistical-, structure-, filter-, and model-based methods. Data-driven-based methods can be divided into two categories: traditional machine learning methods and deep learning techniques. Both data-driven-based and feature-based algorithms have their advantages and disadvantages. Feature-based methods usually have clear algorithmic implications and are therefore easy to control. Suitable features for various application scenarios can be configured for specific objectives. In comparison, feature-based methods are typically effective and simple to implement since they do not rely on massive quantities of data. However, certain difficulties do occur, such as the failure inability to detect small-sized defects and texture irregularities satisfactorily. Data-driven methods are usually implemented by designing certain learnable parameters of the model and then teaching the data model. Training data usually contains images and corresponding annotations that are manually annotated. While data-driven methods exhibit high precision and generalization, they involve a significant amount of learned data and manual annotations. The training phase often involves substantial computational capital and time.
This work focuses on the identification of printing defects on surfaces embossed using randomly spaced three-dimensional (3D) micro-textures. The embossing processes ∗Doctoral Thesis, Division of Systems Science and Informatics, Graduate School of Information Science and Technology, Hokkaido University, SSI-DT79185030, January 6, 2021. produces a very small variety of convex and concave shapes on the surfaces of metals, plastics, or other materials. Changes in the illumination on certain surfaces have a major effect on their appearance, resulting in difficulty in identifying defects. To realize this goal, the use of the multiple paired pixel consistency (MMPC) model was recommended. We first propose a consistency measure based on the correlation of consistent pixel pairs to obtain a robust defect-free model. We then set in motion a new assessment technique to accurately identify defects. Furthermore, a modification method called position-dependent data inhibition (PDI) is proposed to further improve the robustness and performance of the MPPC model.
This overall dissertation is structured as follows.
Chapter 1 introduces the importance of identification of defects and presents the associated works on defect detection. Some challenges in defect detection are discussed. Furthermore, the motivations and contributions of this study are explained.
Chapter 2 introduces the orientation codes (OCs), the use of which could reduce the influence of illumination fluctuations on defect detection; thus, OCs are used as the basis of the proposed method. First, we implement the original version of the OCs and then expand it by presenting two types of operations: a precise spatial differentiation for calculating the codes with a higher resolution and signed difference between any two codes as preparation for building up a more precise statistical model of their difference. Using these operations, we add a more reliable scheme to explain the statistical relationship between a pair of any logotypes pixels.
Chapter 3 introduces the proposed MPPC model in detail, including the fundamental principle and structure of the MPPC model. First, we observe the defect-free images of logotypes to determine the relationship between any pair of pixels in the logotype. We then introduce kurtosis to obtain the potential distributions. After analyzing the distributions, we explain how to pick the supporting pixel for each target pixel and finally construct the MPPC model for each pixel pair.
Chapter 4 provides a discussion of the method for using the proposed MPPC model of the relationship between pixel pairs in the defect-free logotype for identification of several types of logotype defects. Defect detection can be divided into two main stages. First, the status of each pixel pair is determined. We then identify the normal or abnormal states at the corresponding position defined by the elemental MPPC model.
Chapter 5 is focused on the PDI modification suggested on the basis of MPPC to further strengthen the robustness of the MPPC and stabilize its performance. The basic principles and mechanism of the PDI are explored in depth in this chapter. Finally, we verify the capacity of the PDI by appropriate experiments.
Chapter 6 lays out the experimental setup in detail. In this chapter, comparative experiments for the MPPC and MPPC+PDI models using several real defective images and synthesized or artificial defective images under different conditions such as illumination fluctuation and different noise intensities are designed. We test the robustness and efficiency of our methods through these experiments.
The final chapter outlines the key points of this study and presents a discussion of our algorithms. Finally, the strategy and idea for possible future works are discussed.Study on Amoeba-inspired Electronic Computing System for Solving Optimization Problems [an abstract of dissertation and a summary of dissertation review]
http://hdl.handle.net/2115/81605
Title: Study on Amoeba-inspired Electronic Computing System for Solving Optimization Problems [an abstract of dissertation and a summary of dissertation review]
Authors: 斉藤, 健太Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/816052021-03-24T15:00:00Z斉藤, 健太大規模構造物に対する3次元現況反映型モデル生成のための高精度モデリング手法と最適撮影計画手法の開発
http://hdl.handle.net/2115/81601
Title: 大規模構造物に対する3次元現況反映型モデル生成のための高精度モデリング手法と最適撮影計画手法の開発
Authors: 森谷, 亮太
Abstract: 我が国のインフラ建造物の多くは，高度経済成長期に集中的に建設・整備されており，半世紀近く経った現在，老朽化が加速度的に増加している．そのため，膨大なインフラ建造物の戦略的な維持管理および更新することが強く求められており，その解決の切り札として，3次元モデルの活用が期待されている．維持管理作業において，対象物上の変状とその位置を正確に把握することが重要であるが，従来の2次元図面では，即座に把握することが困難である．一方近年，TLS（地上型レーザスキャナ）で計測した3次元点群や，カメラで撮影した画像から，3次元as-is（現況反映型）モデルを自動で生成する技術が現れており，それらを活用し効率的な維持管理作業を行うことが期待されている．そのため，インフラ建造物の現況形状を反映した3次元as-isモデルを，高精度かつ効率的に生成する技術が求められている．
インフラ建造物の現況形状を反映した3次元as-isモデルを高精度かつ効率的に生成するには，対象や3次元モデルの使用目的によって適切な計測手法の選択と，抜けや漏れのない対象表面の計測と高精度なモデル化が必要だが，現状，次のような問題が解決されておらず，技術普及の障害となっている．(1) 3次元計測点群統合時において，誤差の重畳により精度が低下する問題．点群とはTLSで計測された点集合であり，座標値(xyz)と色情報(RGB)を持ち，一回の計測で数千万点の計測点が得られる．一方，物体背後はレーザ光の遮蔽により，計測できずに点群の欠損部となる．このため，欠損部を補完する複数箇所からの計測を行い，計測位置を高精度に推定する点群のレジストレーションと，点群に数学的な曲面を当てはめるモデリングという二つの処理が必要となる．しかし，このレジストレーションとモデリングで各々発生する誤差が重畳し，最終的な3次元as-is モデルの要求精度(例：誤差5mm以内)を満足せず，実業務に使用できない場合がある．(2) 写真計測(SfM-MVS)におけて，3次元モデルの生成効率が低下する問題．カメラで撮影された複数の画像から3次元モデルを生成するには，タイポイント（画像上の対応点を3次元復元した疎な点群）とカメラポーズ（位置・姿勢）とを推定するSfM (Structure from Motion)と高密度な3次元モデルを生成するMVS (Multi-View Stereo)が必要である．しかし，どの位置から何枚画像を撮影すれば,高精度なモデルが生成可能かの事前推定が困難である．そのため，撮影した画像の位置や枚数が不適切であると，カメラポーズの正しい推定が行えない場合や，モデル上に非再構成領域(穴)や大きな形状誤差をもつ品質低下領域を含んだ高密度なモデルが生成される．またこの問題を避けるために，過剰に画像を撮影するとMVS処理に膨大な処理時間がかかってしまう．
上記，2つの問題点に対して，本研究では大規模構造物に対する3次元現況反映型モデル生成のための高精度モデリング手法と最適撮影計画手法の開発を目的とし，主に3つの観点から，問題解決を行う．(1) プラント設備に対して，３次元点群から高精度な3次元as-isモデルを生成するために，単一点群からプラントに多く含まれる円筒配管を抽出し，円筒配管自身をマーカーとして利用した計測点群のレジストレーションと円筒モデリングの同時処理手法を開発することで，それぞれの処理で生じる誤差の重畳を防止し，高精度なモデリングを可能とする．(2) コンクリート製建造物に対して，画像集合から高精度な3次元as-isモデルを生成するために，MVS処理を行わずに最終的に得られるであろう3次元as-isモデルの形状品質をSfMの出力結果から短時間で予測し，さらに，その品質予測結果を基に，低品質と予測される領域の自動抽出を行い，品質を改善できるような追加撮影用のカメラポーズを事前に推定・提示できる技術を開発する．(3) (2)で開発した最適撮影計画手法，ならびにスマートフォンとクラウドシステムを活用した，高精度な3次元モデルを効率的に作成可能な写真計測システムを開発し，工事現場の写真撮影から3次元モデル生成までをその日のうちに完了するワンデーレスポンスの実現を目指す．
以上の手法を，擬似計測点群やプラント設備を計測した実計測点群に適用し，本手法のロバスト性検証や従来手法とのモデリング精度比較を行った．また，実際の橋脚や建造物を撮影した画像集合に対して，本手法を適用し，その有効性を検証した．最後に，実際の工事現場において，ワンデーレスポンスの実現可能性を処理時間の観点から考察した．; Many of infrastructures in japan were intensively constructed during the period of rapid economic growth. Nearly half a century has passed since then, the aging infrastructures are increasing exponentially. Therefore, there is a strong demand for strategic maintenance and updating of enormous of infrastructure buildings, and the use of 3D models is expected as a solution to this problem. In maintenance tasks, it is important for an administrator to understand the correct locations of the deformed region and, however, it is difficult to immediately grasp them in conventional 2D drawing. On the other hand, recently, technologies have been developed to automatically generate 3D as-is models from 3D point clouds measured by TLS (Terrestrial Laser Scanner) and images captured by a camera. Their technologies are expected to be used for efficient maintenance tasks. Thus, there is a need for a technology to generate 3D as-is models that reflect the current geometry of infrastructure buildings with high accuracy and efficiency.
To generate 3D as-is models of infrastructures with accuracy and efficiency, it is necessary to select appropriate scanning approaches and measure object surface without occlusions according to the object or purpose of use, but the following problems prohibit the progress of the technologies; (1) there is the problem that modeling accuracy decrease due to the overlap error in point clouds integration. Point clouds means a set of points captured by TLS and include coordinate values (xyz) and color information (RGB), tens of millions of points can be measured at one time. Whereas, since the region behind the object cannot be measured, the point clouds includes the occlusions. Therefore, we require two process: registration which estimate the scanning positions for the point clouds captured from multiple locations, and modeling which fit a mathematical surface against the point clouds. However, the final as-is model do not satisfy the required accuracy (e.g., error within 5 mm), and the 3D model may not be utilized in practice because the errors of registration and modeling are overlapped: (2) there is the problem that efficiency of the model generation in photogrammetry. SfM (Structure from Motion), which estimates tie points and camera pose, and MVS (Multi-View Stereo), which generates a high-density 3D model, are necessary to generate a 3D model from many images captured by a camera. However, it is difficult to pre-estimate which camera pose and how many images are needed to reconstruct an accurate model. Therefore, if camera position or the number of images is inappropriate, the correct camera poses cannot be estimated, and the dense model with the degraded region (holes) and low-quality region is generated. Moreover, to avoid this problem, MVS processing takes an enormous amount of processing time when redundant images are captured.
For above two problems, the purpose of this research is to develop a high-quality modeling method and view planning method for generating 3D as-is model reconstruction in large-scale environments. We solve the problems from the following three approaches; (1) To generate accurate 3D as-is models of plant facilities from point clouds, we first extract cylindrical pipes in the plant from a plant point cloud, and develop a method of simultaneous registration and modeling using the cylindrical pipes as markers. The method is able to prevent the overlapping of the errors in each process and reconstruct high-accuracy models: (2) To generate accurate 3D as-is model from a set of images of a concrete building, we predict the geometric quality of 3D as-is model which will be obtained without MVS process only from the SfM result in a short time. Moreover, based on the quality prediction, we develop the algorithm for extracting the regions which are predicted as low-quality and estimating the additional camera poses which can improve the quality in advance: (3) we develop the photogrammetry process which can efficiently generate high-quality 3D models by integrating a smartphone, cloud service, and computer-assisted best-view guidance for optimal camera poses developed in (2). The system aims to achieve a one-day response that completes the process from photography to 3D model generation on the same day.
We applied the above methods to pseudo point clouds and actual point clouds of plant facilities to verify the robustness of the method and to compare with conventional methods about modeling accuracy. Moreover, we also applied the method to a set of images captured from concrete bridge columns and buildings and verified effectiveness of our study. Finally, the feasibility of one-day response in an actual construction site is discussed in terms of processing time.Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/816012021-03-24T15:00:00Z森谷, 亮太我が国のインフラ建造物の多くは，高度経済成長期に集中的に建設・整備されており，半世紀近く経った現在，老朽化が加速度的に増加している．そのため，膨大なインフラ建造物の戦略的な維持管理および更新することが強く求められており，その解決の切り札として，3次元モデルの活用が期待されている．維持管理作業において，対象物上の変状とその位置を正確に把握することが重要であるが，従来の2次元図面では，即座に把握することが困難である．一方近年，TLS（地上型レーザスキャナ）で計測した3次元点群や，カメラで撮影した画像から，3次元as-is（現況反映型）モデルを自動で生成する技術が現れており，それらを活用し効率的な維持管理作業を行うことが期待されている．そのため，インフラ建造物の現況形状を反映した3次元as-isモデルを，高精度かつ効率的に生成する技術が求められている．
インフラ建造物の現況形状を反映した3次元as-isモデルを高精度かつ効率的に生成するには，対象や3次元モデルの使用目的によって適切な計測手法の選択と，抜けや漏れのない対象表面の計測と高精度なモデル化が必要だが，現状，次のような問題が解決されておらず，技術普及の障害となっている．(1) 3次元計測点群統合時において，誤差の重畳により精度が低下する問題．点群とはTLSで計測された点集合であり，座標値(xyz)と色情報(RGB)を持ち，一回の計測で数千万点の計測点が得られる．一方，物体背後はレーザ光の遮蔽により，計測できずに点群の欠損部となる．このため，欠損部を補完する複数箇所からの計測を行い，計測位置を高精度に推定する点群のレジストレーションと，点群に数学的な曲面を当てはめるモデリングという二つの処理が必要となる．しかし，このレジストレーションとモデリングで各々発生する誤差が重畳し，最終的な3次元as-is モデルの要求精度(例：誤差5mm以内)を満足せず，実業務に使用できない場合がある．(2) 写真計測(SfM-MVS)におけて，3次元モデルの生成効率が低下する問題．カメラで撮影された複数の画像から3次元モデルを生成するには，タイポイント（画像上の対応点を3次元復元した疎な点群）とカメラポーズ（位置・姿勢）とを推定するSfM (Structure from Motion)と高密度な3次元モデルを生成するMVS (Multi-View Stereo)が必要である．しかし，どの位置から何枚画像を撮影すれば,高精度なモデルが生成可能かの事前推定が困難である．そのため，撮影した画像の位置や枚数が不適切であると，カメラポーズの正しい推定が行えない場合や，モデル上に非再構成領域(穴)や大きな形状誤差をもつ品質低下領域を含んだ高密度なモデルが生成される．またこの問題を避けるために，過剰に画像を撮影するとMVS処理に膨大な処理時間がかかってしまう．
上記，2つの問題点に対して，本研究では大規模構造物に対する3次元現況反映型モデル生成のための高精度モデリング手法と最適撮影計画手法の開発を目的とし，主に3つの観点から，問題解決を行う．(1) プラント設備に対して，３次元点群から高精度な3次元as-isモデルを生成するために，単一点群からプラントに多く含まれる円筒配管を抽出し，円筒配管自身をマーカーとして利用した計測点群のレジストレーションと円筒モデリングの同時処理手法を開発することで，それぞれの処理で生じる誤差の重畳を防止し，高精度なモデリングを可能とする．(2) コンクリート製建造物に対して，画像集合から高精度な3次元as-isモデルを生成するために，MVS処理を行わずに最終的に得られるであろう3次元as-isモデルの形状品質をSfMの出力結果から短時間で予測し，さらに，その品質予測結果を基に，低品質と予測される領域の自動抽出を行い，品質を改善できるような追加撮影用のカメラポーズを事前に推定・提示できる技術を開発する．(3) (2)で開発した最適撮影計画手法，ならびにスマートフォンとクラウドシステムを活用した，高精度な3次元モデルを効率的に作成可能な写真計測システムを開発し，工事現場の写真撮影から3次元モデル生成までをその日のうちに完了するワンデーレスポンスの実現を目指す．
以上の手法を，擬似計測点群やプラント設備を計測した実計測点群に適用し，本手法のロバスト性検証や従来手法とのモデリング精度比較を行った．また，実際の橋脚や建造物を撮影した画像集合に対して，本手法を適用し，その有効性を検証した．最後に，実際の工事現場において，ワンデーレスポンスの実現可能性を処理時間の観点から考察した．
Many of infrastructures in japan were intensively constructed during the period of rapid economic growth. Nearly half a century has passed since then, the aging infrastructures are increasing exponentially. Therefore, there is a strong demand for strategic maintenance and updating of enormous of infrastructure buildings, and the use of 3D models is expected as a solution to this problem. In maintenance tasks, it is important for an administrator to understand the correct locations of the deformed region and, however, it is difficult to immediately grasp them in conventional 2D drawing. On the other hand, recently, technologies have been developed to automatically generate 3D as-is models from 3D point clouds measured by TLS (Terrestrial Laser Scanner) and images captured by a camera. Their technologies are expected to be used for efficient maintenance tasks. Thus, there is a need for a technology to generate 3D as-is models that reflect the current geometry of infrastructure buildings with high accuracy and efficiency.
To generate 3D as-is models of infrastructures with accuracy and efficiency, it is necessary to select appropriate scanning approaches and measure object surface without occlusions according to the object or purpose of use, but the following problems prohibit the progress of the technologies; (1) there is the problem that modeling accuracy decrease due to the overlap error in point clouds integration. Point clouds means a set of points captured by TLS and include coordinate values (xyz) and color information (RGB), tens of millions of points can be measured at one time. Whereas, since the region behind the object cannot be measured, the point clouds includes the occlusions. Therefore, we require two process: registration which estimate the scanning positions for the point clouds captured from multiple locations, and modeling which fit a mathematical surface against the point clouds. However, the final as-is model do not satisfy the required accuracy (e.g., error within 5 mm), and the 3D model may not be utilized in practice because the errors of registration and modeling are overlapped: (2) there is the problem that efficiency of the model generation in photogrammetry. SfM (Structure from Motion), which estimates tie points and camera pose, and MVS (Multi-View Stereo), which generates a high-density 3D model, are necessary to generate a 3D model from many images captured by a camera. However, it is difficult to pre-estimate which camera pose and how many images are needed to reconstruct an accurate model. Therefore, if camera position or the number of images is inappropriate, the correct camera poses cannot be estimated, and the dense model with the degraded region (holes) and low-quality region is generated. Moreover, to avoid this problem, MVS processing takes an enormous amount of processing time when redundant images are captured.
For above two problems, the purpose of this research is to develop a high-quality modeling method and view planning method for generating 3D as-is model reconstruction in large-scale environments. We solve the problems from the following three approaches; (1) To generate accurate 3D as-is models of plant facilities from point clouds, we first extract cylindrical pipes in the plant from a plant point cloud, and develop a method of simultaneous registration and modeling using the cylindrical pipes as markers. The method is able to prevent the overlapping of the errors in each process and reconstruct high-accuracy models: (2) To generate accurate 3D as-is model from a set of images of a concrete building, we predict the geometric quality of 3D as-is model which will be obtained without MVS process only from the SfM result in a short time. Moreover, based on the quality prediction, we develop the algorithm for extracting the regions which are predicted as low-quality and estimating the additional camera poses which can improve the quality in advance: (3) we develop the photogrammetry process which can efficiently generate high-quality 3D models by integrating a smartphone, cloud service, and computer-assisted best-view guidance for optimal camera poses developed in (2). The system aims to achieve a one-day response that completes the process from photography to 3D model generation on the same day.
We applied the above methods to pseudo point clouds and actual point clouds of plant facilities to verify the robustness of the method and to compare with conventional methods about modeling accuracy. Moreover, we also applied the method to a set of images captured from concrete bridge columns and buildings and verified effectiveness of our study. Finally, the feasibility of one-day response in an actual construction site is discussed in terms of processing time.Control of Formation and Magnetic Domain Structures in Selectively-Grown MnAs Nanostructures
http://hdl.handle.net/2115/81591
Title: Control of Formation and Magnetic Domain Structures in Selectively-Grown MnAs Nanostructures
Authors: 堀口, 竜麻Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/815912021-03-24T15:00:00Z堀口, 竜麻2光子顕微鏡法を用いた補償光学による生体組織深部の可視化解析
http://hdl.handle.net/2115/81545
Title: 2光子顕微鏡法を用いた補償光学による生体組織深部の可視化解析
Authors: 山口, 和志Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/815452021-03-24T15:00:00Z山口, 和志大規模構造物に対する3次元現況反映型モデル生成のための高精度モデリング手法と最適撮影計画手法の開発 [論文内容及び審査の要旨]
http://hdl.handle.net/2115/81542
Title: 大規模構造物に対する3次元現況反映型モデル生成のための高精度モデリング手法と最適撮影計画手法の開発 [論文内容及び審査の要旨]
Authors: 森谷, 亮太Wed, 24 Mar 2021 15:00:00 GMThttp://hdl.handle.net/2115/815422021-03-24T15:00:00Z森谷, 亮太