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发表于 2025-3-21 18:33:32 | 显示全部楼层 |阅读模式
书目名称Group-Theoretical Methods in Image Understanding
编辑Kenichi Kanatani
视频video
丛书名称Springer Series in Information Sciences
图书封面Titlebook: ;
出版日期Textbook 1990
版次1
doihttps://doi.org/10.1007/978-3-642-61275-6
isbn_ebook978-3-642-61275-6Series ISSN 0720-678X
issn_series 0720-678X
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发表于 2025-3-21 23:56:56 | 显示全部楼层
发表于 2025-3-22 02:12:57 | 显示全部楼层
Algebraic Invariance of Image Characteristicsra rotation. Such expressions are called .. We will also show that if two images depict one and the same scene viewed from two different camera angles, the camera rotation that transforms one image into the other can be reconstructed from a small number of image characteristics.
发表于 2025-3-22 06:14:58 | 显示全部楼层
发表于 2025-3-22 09:46:33 | 显示全部楼层
https://doi.org/10.1007/978-3-642-49822-0ine which we call “Weyl’s thesis”, we show that the geometrical meanings of involved quantities become clear if the 3D recovery equations are written in terms of invariants. We also see that analytical solutions often emerge themselves. To illustrate this, we apply our method to optical flow analysis and the shape-from-texture problem.
发表于 2025-3-22 13:21:40 | 显示全部楼层
发表于 2025-3-22 20:36:41 | 显示全部楼层
Richard Bellamy,Justus Schönlauometrical structures of the “scene space” and the “image space” by means of tensor calculus. Then, we analyze invariance properties of “linear functionals” of images, which we call ., and show how they are used for identification and classification of shapes.
发表于 2025-3-23 00:47:14 | 显示全部楼层
发表于 2025-3-23 03:21:24 | 显示全部楼层
The Significance of Philosophical Fallacies,efinitions of . and . in terms of the theory of distributions and differential geometry. Then, we present numerical schemes for solving the resulting 3D recovery equations. We also give some numerical examples for synthetic data.
发表于 2025-3-23 08:03:27 | 显示全部楼层
Subjective Probability and Common Knowledgent data. Our optimization is achived by solving a set of linear equations; no searches and iterations are necessary. This technique is first applied to the problem of shape from motion and then to the 3D recovery based on the rectangularity hypothesis and the parallelism hypothesis.
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