3D Computer Vision [electronic resource] : Foundations and Advanced Methodologies / by Yu-Jin Zhang.

Por: Zhang, Yu-Jin [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoEditor: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XVI, 469 p. 218 illus., 178 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789811976032Tema(s): Computer vision | Image processing -- Digital techniques | Image processing | Computer Vision | Computer Imaging, Vision, Pattern Recognition and Graphics | Image ProcessingFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.37 Clasificación LoC:TA1634Recursos en línea: Libro electrónicoTexto
Contenidos:
Chapter 1 Introduction -- Chapter 2 Camera Imaging and Calibration -- Chapter 3 Depth Image Acquisition -- Chapter 4 Binocular Stereo Vision -- Chapter 5 Multi-Ocular Stereo Vision -- Chapter 6 Monocular Multi-Image Scene Restoration -- Chapter 7 Monocular Single-Image Scene Restoration -- Chapter 8 Point Cloud Data Processing -- Chapter 9 Simultaneous Location and Mapping -- Chapter 10 Generalized Matching -- Chapter 11 Understanding of Spatial-Temporal Behavior.
En: Springer Nature eBookResumen: This book offers a comprehensive and unbiased introduction to 3D Computer Vision, ranging from its foundations and essential principles to advanced methodologies and technologies. Divided into 11 chapters, it covers the main workflow of 3D computer vision as follows: camera imaging and calibration models; various modes and means of 3D image acquisition; binocular, trinocular and multi-ocular stereo vision matching techniques; monocular single-image and multi-image scene restoration methods; point cloud data processing and modeling; simultaneous location and mapping; generalized image and scene matching; and understanding spatial-temporal behavior. Each topic is addressed in a uniform manner: the dedicated chapter first covers the essential concepts and basic principles before presenting a selection of typical, specific methods and practical techniques. In turn, it introduces readers to the most important recent developments, especially in the last three years. This approach allows them to quickly familiarize themselves with the subject, implement the techniques discussed, and design or improve their own methods for specific applications. The book can be used as a textbook for graduate courses in computer science, computer engineering, electrical engineering, data science, and related subjects. It also offers a valuable reference guide for researchers and practitioners alike.
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Chapter 1 Introduction -- Chapter 2 Camera Imaging and Calibration -- Chapter 3 Depth Image Acquisition -- Chapter 4 Binocular Stereo Vision -- Chapter 5 Multi-Ocular Stereo Vision -- Chapter 6 Monocular Multi-Image Scene Restoration -- Chapter 7 Monocular Single-Image Scene Restoration -- Chapter 8 Point Cloud Data Processing -- Chapter 9 Simultaneous Location and Mapping -- Chapter 10 Generalized Matching -- Chapter 11 Understanding of Spatial-Temporal Behavior.

This book offers a comprehensive and unbiased introduction to 3D Computer Vision, ranging from its foundations and essential principles to advanced methodologies and technologies. Divided into 11 chapters, it covers the main workflow of 3D computer vision as follows: camera imaging and calibration models; various modes and means of 3D image acquisition; binocular, trinocular and multi-ocular stereo vision matching techniques; monocular single-image and multi-image scene restoration methods; point cloud data processing and modeling; simultaneous location and mapping; generalized image and scene matching; and understanding spatial-temporal behavior. Each topic is addressed in a uniform manner: the dedicated chapter first covers the essential concepts and basic principles before presenting a selection of typical, specific methods and practical techniques. In turn, it introduces readers to the most important recent developments, especially in the last three years. This approach allows them to quickly familiarize themselves with the subject, implement the techniques discussed, and design or improve their own methods for specific applications. The book can be used as a textbook for graduate courses in computer science, computer engineering, electrical engineering, data science, and related subjects. It also offers a valuable reference guide for researchers and practitioners alike.

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