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001440030 020__ $$a9811649391$$q(electronic bk.)
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001440030 0247_ $$a10.1007/978-981-16-4939-4$$2doi
001440030 035__ $$aSP(OCoLC)1272854923
001440030 040__ $$aYDX$$beng$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCF$$dOCLCO$$dOCLCQ$$dOCLCO$$dCOM$$dOCLCQ
001440030 0411_ $$aeng$$hchi
001440030 049__ $$aISEA
001440030 050_4 $$aTK5103.4895
001440030 08204 $$a621.384$$223
001440030 1001_ $$aGao, Xiang.
001440030 24510 $$aIntroduction to Visual SLAM :$$bfrom theory to practice /$$cXiang Gao, Tao Zhang.
001440030 260__ $$aSingapore :$$bSpringer,$$c[2022]
001440030 300__ $$a1 online resource
001440030 336__ $$atext$$btxt$$2rdacontent
001440030 337__ $$acomputer$$bc$$2rdamedia
001440030 338__ $$aonline resource$$bcr$$2rdacarrier
001440030 5050_ $$aIntro -- Preface -- What is This Book Talking About? -- How to Use This Book? -- Source Code -- Targeted Readers -- Style -- Exercises (Self-test Questions) -- Acknowledgments -- Contents -- Part I Fundamental Knowledge -- 1 Introduction to SLAM -- 1.1 Meet ``Little Carrot'' -- 1.1.1 Monocular Camera -- 1.1.2 Stereo Cameras and RGB-D Cameras -- 1.2 Classical Visual SLAM Framework -- 1.2.1 Visual Odometry -- 1.2.2 Backend Optimization -- 1.2.3 Loop Closing -- 1.2.4 Mapping -- 1.3 Mathematical Formulation of SLAM Problems -- 1.4 Practice: Basics -- 1.4.1 Installing Linux -- 1.4.2 Hello SLAM
001440030 5058_ $$a1.4.3 Use CMake -- 1.4.4 Use Libraries -- 1.4.5 Use IDE -- 2 3D Rigid Body Motion -- 2.1 Rotation Matrix -- 2.1.1 Points, Vectors, and Coordinate Systems -- 2.1.2 Euclidean Transforms Between Coordinate Systems -- 2.1.3 Transform Matrix and Homogeneous Coordinates -- 2.2 Practice: Use Eigen -- 2.3 Rotation Vectors and the Euler Angles -- 2.3.1 Rotation Vectors -- 2.3.2 Euler Angles -- 2.4 Quaternions -- 2.4.1 Quaternion Operations -- 2.4.2 Use Quaternion to Represent a Rotation -- 2.4.3 Conversion of Quaternions to Other Rotation Representations -- 2.5 Affine and Projective Transformation
001440030 5058_ $$a2.6 Practice: Eigen Geometry Module -- 2.6.1 Data Structure of the Eigen Geometry Module -- 2.6.2 Coordinate Transformation Example -- 2.7 Visualization Demo -- 2.7.1 Plotting Trajectory -- 2.7.2 Displaying Camera Pose -- 3 Lie Group and Lie Algebra -- 3.1 Basics of Lie Group and Lie Algebra -- 3.1.1 Group -- 3.1.2 Introduction of the Lie Algebra -- 3.1.3 The Definition of Lie Algebra -- 3.1.4 Lie Algebra mathfrakso(3) -- 3.1.5 Lie Algebra mathfrakse(3) -- 3.2 Exponential and Logarithmic Mapping -- 3.2.1 Exponential Map of SO(3) -- 3.2.2 Exponential Map of SE(3)
001440030 5058_ $$a3.3 Lie Algebra Derivation and Perturbation Model -- 3.3.1 BCH Formula and Its Approximation -- 3.3.2 Derivative on SO(3) -- 3.3.3 Derivative Model -- 3.3.4 Perturbation Model -- 3.3.5 Derivative on SE(3) -- 3.4 Practice: Sophus -- 3.4.1 Basic Usage of Sophus -- 3.4.2 Example: Evaluating the Trajectory -- 3.5 Similar Transform Group and Its Lie Algebra -- 3.6 Summary -- 4 Cameras and Images -- 4.1 Pinhole Camera Models -- 4.1.1 Pinhole Camera Geometry -- 4.1.2 Distortion -- 4.1.3 Stereo Cameras -- 4.1.4 RGB-D Cameras -- 4.2 Images -- 4.3 Practice: Images in Computer Vision
001440030 5058_ $$a4.3.1 Basic Usage of OpenCV -- 4.3.2 Basic OpenCV Images Operations -- 4.3.3 Image Undistortion -- 4.4 Practice: 3D Vision -- 4.4.1 Stereo Vision -- 4.4.2 RGB-D Vision -- 5 Nonlinear Optimization -- 5.1 State Estimation -- 5.1.1 From Batch State Estimation to Least-Square -- 5.1.2 Introduction to Least-Squares -- 5.1.3 Example: Batch State Estimation -- 5.2 Nonlinear Least-Square Problem -- 5.2.1 The First and Second-Order Method -- 5.2.2 The Gauss-Newton Method -- 5.2.3 The Levernberg-Marquatdt Method -- 5.2.4 Conclusion -- 5.3 Practice: Curve Fitting -- 5.3.1 Curve Fitting with Gauss-Newton
001440030 506__ $$aAccess limited to authorized users.
001440030 520__ $$aThis book offers a systematic and comprehensive introduction to the visual simultaneous localization and mapping (vSLAM) technology, which is a fundamental and essential component for many applications in robotics, wearable devices, and autonomous driving vehicles. The book starts from very basic mathematic background knowledge such as 3D rigid body geometry, the pinhole camera projection model, and nonlinear optimization techniques, before introducing readers to traditional computer vision topics like feature matching, optical flow, and bundle adjustment. The book employs a light writing style, instead of the rigorous yet dry approach that is common in academic literature. In addition, it includes a wealth of executable source code with increasing difficulty to help readers understand and use the practical techniques. The book can be used as a textbook for senior undergraduate or graduate students, or as reference material for researchers and engineers in related areas.
001440030 650_0 $$aWireless localization.
001440030 650_0 $$aComputer vision.
001440030 650_0 $$aSensor networks.
001440030 650_6 $$aLocalisation sans fil.
001440030 650_6 $$aVision par ordinateur.
001440030 650_6 $$aRéseaux de capteurs.
001440030 655_0 $$aElectronic books.
001440030 7001_ $$aZhang, Tao.
001440030 77608 $$iPrint version:$$aGao, Xiang.$$tIntroduction to Visual SLAM.$$dSingapore : Springer, [2022]$$z9811649383$$z9789811649387$$w(OCoLC)1259049335
001440030 852__ $$bebk
001440030 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-4939-4$$zOnline Access$$91397441.1
001440030 909CO $$ooai:library.usi.edu:1440030$$pGLOBAL_SET
001440030 980__ $$aBIB
001440030 980__ $$aEBOOK
001440030 982__ $$aEbook
001440030 983__ $$aOnline
001440030 994__ $$a92$$bISE