Line Drawing Interpretation

• Κύριος συγγραφέας: Cooper, Martin (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: London : Springer London, 2008.
• Θέματα: Computer science.; Mathematical logic.; Computer science > Mathematics.; Computer graphics.; Image processing.; Computer-aided engineering.; Cognitive psychology.; Computer Science.; Image Processing and Computer Vision.; Computer Imaging, Vision, Pattern Recognition and Graphics.; Computer-Aided Engineering (CAD, CAE) and Design.; Mathematical Logic and Formal Languages.; Cognitive Psychology.; Discrete Mathematics in Computer Science.

 The computer interpretation of line drawings is a classic problem in artificial intelligence and has inspired the development of some fundamental AI tools, including constraint propagation, probabilistic relaxation, tractable constraints, and (most recently) local simplification of optimisation problems. Based on the author’s considerable research experience, this book looks at line drawing interpretation and constraint satisfaction, covering several landmark results in the field. It contains state-of-the-art reviews of work in both drawing interpretation and discrete optimisation, and is not just restricted to drawings of polyhedral objects, but also covers complex curved objects. Its novel approach to drawing interpretation combines new constraints with recent advances in soft constraint programming. The book will become a standard reference in the field with its coverage of many theoretical results with formal proofs, particularly concerning necessary-and-sufficient conditions for realizability, simplification operations for combinatorial problems and tractability of drawing interpretation. Martin Cooper makes this fascinating topic accessible not only to computer scientists, but also to mathematicians, psychologists and cognitive scientists – indeed to anyone intrigued by optical illusions and impossible or ambiguous figures. 

 Impossible Pictures -- Labeling Line Drawings of Polyhedra -- Discrete In°ation Using Cubic Corners -- A Rich Labeling Scheme for Curved Objects -- Depth Recovery Through Linear Algebra -- Wireframe Projections -- Simplification of Combinatorial Problems -- Tractability of Drawing Interpretation -- 3D Reconstruction of Ambiguous Pictures.