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Classification and Characterization of Image Acquisition for 3D Scene Visualization and Reconstruction Applications

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2032))

Abstract

This paper discusses the techniques of image acquisition for 3D scene visualization and reconstruction applications (3DSVR). The existing image acquisition approaches in 3DSVR applications are briefly reviewed. There are still lacks of studies about what principles are essential in the design and how we can characterize the limitations of an image acquisition model in a formal way. This paper addresses some of the main characteristics of existing image acquisition approaches, summarized through a classification scheme and illustrated with many examples. The results of the classification lead to general characterizations in establishing the notions (basic components) for design, analysis and assessment of image acquisition models. The notions introduced include: focal set, receptor set, reflector set etc. The formal definitions of the notions and the exploration of relationships among the components are given. Various examples are provided for demonstrating the flexibility and compactness in characterizing different types of image acquisition models such as concentric, polycentric, cataoptrical panoramas etc. The observations, important issues, and future directions from this study are also elaborated.

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© 2001 Springer-Verlag Berlin Heidelberg

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Wei, S.K., Huang, F., Klette, R. (2001). Classification and Characterization of Image Acquisition for 3D Scene Visualization and Reconstruction Applications. In: Klette, R., Gimel’farb, G., Huang, T. (eds) Multi-Image Analysis. Lecture Notes in Computer Science, vol 2032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45134-X_6

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  • DOI: https://doi.org/10.1007/3-540-45134-X_6

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  • Print ISBN: 978-3-540-42122-1

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