| 书目名称 | Representations and Techniques for 3D Object Recognition and Scene Interpretation | | 编辑 | Derek Hoiem,Silvio Savarese | | 视频video | | | 丛书名称 | Synthesis Lectures on Artificial Intelligence and Machine Learning | | 图书封面 |  | | 描述 | One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to c | | 出版日期 | Book 2011 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01557-1 | | isbn_softcover | 978-3-031-00429-2 | | isbn_ebook | 978-3-031-01557-1Series ISSN 1939-4608 Series E-ISSN 1939-4616 | | issn_series | 1939-4608 | | copyright | Springer Nature Switzerland AG 2011 |
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发表于 2025-3-21 17:53:08
