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Titlebook: Control Grid Motion Estimation for Efficient Application of Optical Flow; Christine M. Zwart,David H. Frakes Book 2013 Springer Nature Swi

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發(fā)表于 2025-3-21 19:06:10 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Control Grid Motion Estimation for Efficient Application of Optical Flow
編輯Christine M. Zwart,David H. Frakes
視頻videohttp://file.papertrans.cn/238/237245/237245.mp4
叢書名稱Synthesis Lectures on Algorithms and Software in Engineering
圖書封面Titlebook: Control Grid Motion Estimation for Efficient Application of Optical Flow;  Christine M. Zwart,David H. Frakes Book 2013 Springer Nature Swi
描述Motion estimation is a long-standing cornerstone of image and video processing. Most notably, motion estimation serves as the foundation for many of today‘s ubiquitous video coding standards including H.264. Motion estimators also play key roles in countless other applications that serve the consumer, industrial, biomedical, and military sectors. Of the many available motion estimation techniques, optical flow is widely regarded as most flexible. The flexibility offered by optical flow is particularly useful for complex registration and interpolation problems, but comes at a considerable computational expense. As the volume and dimensionality of data that motion estimators are applied to continue to grow, that expense becomes more and more costly. Control grid motion estimators based on optical flow can accomplish motion estimation with flexibility similar to pure optical flow, but at a fraction of the computational expense. Control grid methods also offer the added benefit of representing motion far more compactly than pure optical flow. This booklet explores control grid motion estimation and provides implementations of the approach that apply to data of multiple dimensionalities
出版日期Book 2013
版次1
doihttps://doi.org/10.1007/978-3-031-01520-5
isbn_softcover978-3-031-00392-9
isbn_ebook978-3-031-01520-5Series ISSN 1938-1727 Series E-ISSN 1938-1735
issn_series 1938-1727
copyrightSpringer Nature Switzerland AG 2013
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 21:16:29 | 只看該作者
1938-1727 many of today‘s ubiquitous video coding standards including H.264. Motion estimators also play key roles in countless other applications that serve the consumer, industrial, biomedical, and military sectors. Of the many available motion estimation techniques, optical flow is widely regarded as most
板凳
發(fā)表于 2025-3-22 04:22:37 | 只看該作者
https://doi.org/10.1007/978-3-642-88633-1originally presented, a control grid is a mesh of contiguous quadrilaterals, the vertices of which are mapped to the vertices of a regular lattice of contiguous rectangles as shown in Figure 2.1. Control grid interpolation describes the process by which points within the elements of the control grid are mapped between the input and output images.
地板
發(fā)表于 2025-3-22 08:37:43 | 只看該作者
Zur Psychopathologie und Psychiatrie,ain underdetermined optimization problems. While the origins of optical flow (and its most common applications) are in the context of video and motion estimation, the fundamental mathematics of intensity matching have widespread applications. In this chapter we explore several contexts for intensity-based registration.
5#
發(fā)表于 2025-3-22 10:15:42 | 只看該作者
Introduction, review the considerations, applications, and history of motion estimation techniques for video registration before exploring two popular methods (block-matching and optical flow). At the end of the chapter, we briefly cover conventions used in the remainder of the book and preview its organization.
6#
發(fā)表于 2025-3-22 14:52:59 | 只看該作者
Control Grid Interpolation (CGI),originally presented, a control grid is a mesh of contiguous quadrilaterals, the vertices of which are mapped to the vertices of a regular lattice of contiguous rectangles as shown in Figure 2.1. Control grid interpolation describes the process by which points within the elements of the control grid are mapped between the input and output images.
7#
發(fā)表于 2025-3-22 21:01:58 | 只看該作者
Application of CGI to Registration Problems,ain underdetermined optimization problems. While the origins of optical flow (and its most common applications) are in the context of video and motion estimation, the fundamental mathematics of intensity matching have widespread applications. In this chapter we explore several contexts for intensity-based registration.
8#
發(fā)表于 2025-3-22 21:12:35 | 只看該作者
Theorie der Versicherungsfunktionen, review the considerations, applications, and history of motion estimation techniques for video registration before exploring two popular methods (block-matching and optical flow). At the end of the chapter, we briefly cover conventions used in the remainder of the book and preview its organization.
9#
發(fā)表于 2025-3-23 02:28:04 | 只看該作者
Introduction,ration of video frames or images. Techniques for registration and motion estimation are widely available, and methods exist for diverse combinations of flexibility, resolution, and assumptions. Method selection involves trade-offs in accuracy, sensitivity, and efficiency. In this chapter, we briefly
10#
發(fā)表于 2025-3-23 07:31:51 | 只看該作者
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