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Titlebook: Geometric Constraints for Object Detection and Delineation; Jefferey Shufelt Book 2000 Springer Science+Business Media New York 2000 3D.Na

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發(fā)表于 2025-3-21 18:01:41 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Geometric Constraints for Object Detection and Delineation
編輯Jefferey Shufelt
視頻videohttp://file.papertrans.cn/384/383488/383488.mp4
叢書名稱The Springer International Series in Engineering and Computer Science
圖書封面Titlebook: Geometric Constraints for Object Detection and Delineation;  Jefferey Shufelt Book 2000 Springer Science+Business Media New York 2000 3D.Na
描述The ability to extract generic 3D objects from images is acrucial step towards automation of a variety of problems incartographic database compilation, industrial inspection and assembly,and autonomous navigation. Many of these problem domains do not havestrong constraints on object shape or scene content, presentingserious obstacles for the development of robust object detection anddelineation techniques. .Geometric Constraints for ObjectDetection. .and Delineation. addresses these problems with asuite of novel methods and techniques for detecting and delineatinggeneric objects in images of complex scenes, and applies them to thespecific task of building detection and delineation from monocularaerial imagery. .PIVOT, the fully automated system implementing these techniques, isquantitatively evaluated on 83 images covering 18 test scenes, andcompared to three existing systems for building extraction. Theresults highlight the performance improvements possible with rigorousphotogrammetric camera modeling, primitive-based objectrepresentations, and geometric constraints derived from theircombination. PIVOT‘s performance illustrates the implications of aclearly articulated set of philo
出版日期Book 2000
關鍵詞3D; Navigation; automation; autonom; database; digital elevation model; modeling; performance; remote sensin
版次1
doihttps://doi.org/10.1007/978-1-4615-5273-4
isbn_softcover978-1-4613-7405-3
isbn_ebook978-1-4615-5273-4Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 2000
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沙發(fā)
發(fā)表于 2025-3-21 22:15:13 | 只看該作者
Book 2000g extraction. Theresults highlight the performance improvements possible with rigorousphotogrammetric camera modeling, primitive-based objectrepresentations, and geometric constraints derived from theircombination. PIVOT‘s performance illustrates the implications of aclearly articulated set of philo
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發(fā)表于 2025-3-22 01:35:54 | 只看該作者
Geometric Constraints for Object Detection and Delineation
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發(fā)表于 2025-3-22 20:32:22 | 只看該作者
Primitives and Vanishing Points, primitive volumetric forms as building blocks for complex object models. The idea behind such a strategy is that these simple primitive forms can be readily extracted from image data, while still maintaining expressive power by combination into complex shapes. This approach raises two natural questions:
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發(fā)表于 2025-3-23 00:15:55 | 只看該作者
Geometric Constraints for Hypothesis Generation,provide estimates of line orientation in object space; qualitatively, they can be employed to constrain the search for primitives in hypothesis space. The techniques developed in Chapter 3 exploited the primitive geometry to hypothesize plausible 3D orientations, or labels, for each line segment in the image.
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發(fā)表于 2025-3-23 01:55:07 | 只看該作者
India Business Etiquette and Culture,This chapter briefly surveys the research accomplishments of the work described in this book as a whole, and addresses various issues raised during the course of the work in a section on future research.
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發(fā)表于 2025-3-23 08:46:24 | 只看該作者
Conclusions,This chapter briefly surveys the research accomplishments of the work described in this book as a whole, and addresses various issues raised during the course of the work in a section on future research.
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