| 書目名稱 | Front-End Vision and Multi-Scale Image Analysis |
| 副標(biāo)題 | Multi-scale Computer |
| 編輯 | Bart M. Romeny |
| 視頻video | http://file.papertrans.cn/350/349060/349060.mp4 |
| 概述 | A breakthrough in interactive teaching of multi-scale methods for image analysis.For Mathematica 5.0 an upgrade is available for free download. |
| 叢書名稱 | Computational Imaging and Vision |
| 圖書封面 |  |
| 描述 | Many approaches have been proposed to solve the problem of finding the optic flow field of an image sequence. Three major classes of optic flow computation techniques can discriminated (see for a good overview Beauchemin and Barron IBeauchemin19951): gradient based (or differential) methods; phase based (or frequency domain) methods; correlation based (or area) methods; feature point (or sparse data) tracking methods; In this chapter we compute the optic flow as a dense optic flow field with a multi scale differential method. The method, originally proposed by Florack and Nielsen [Florack1998a] is known as the Multiscale Optic Flow Constrain Equation (MOFCE). This is a scale space version of the well known computer vision implementation of the optic flow constraint equation, as originally proposed by Horn and Schunck [Horn1981]. This scale space variation, as usual, consists of the introduction of the aperture of the observation in the process. The application to stereo has been described by Maas et al. [Maas 1995a, Maas 1996a]. Of course, difficulties arise when structure emerges or disappears, such as with occlusion, cloud formation etc. Then knowledge is needed about the process |
| 出版日期 | Book 2003 |
| 關(guān)鍵詞 | computer vision; Diffusion; image analysis; kernel; knowledge; Pattern Matching; tracking |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4020-8840-7 |
| isbn_softcover | 978-1-4020-1507-6 |
| isbn_ebook | 978-1-4020-8840-7Series ISSN 1381-6446 |
| issn_series | 1381-6446 |
| copyright | Springer Science+Business Media B.V. 2003 |
|Archiver|手機(jī)版|小黑屋|
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