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Titlebook: Handbook of Mathematical Models in Computer Vision; Nikos Paragios,Yunmei Chen,Olivier Faugeras Book 2006 Springer-Verlag US 2006 3D.3D gr

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發(fā)表于 2025-3-21 17:05:32 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Handbook of Mathematical Models in Computer Vision
編輯Nikos Paragios,Yunmei Chen,Olivier Faugeras
視頻videohttp://file.papertrans.cn/422/421626/421626.mp4
概述The most comprehensive, up-to-date treatment of computational vision topics.Six thematic areas provide answers to the most dominant questions of computational vision
圖書(shū)封面Titlebook: Handbook of Mathematical Models in Computer Vision;  Nikos Paragios,Yunmei Chen,Olivier Faugeras Book 2006 Springer-Verlag US 2006 3D.3D gr
描述Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math- ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro- ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr‘s theory v^as a pioneering step tov^ards understanding visual percep- tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet- ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emer
出版日期Book 2006
關(guān)鍵詞3D; 3D graphics; Alignment; Analysis; STATISTICA; Stereo; algorithms; computer; image analysis; image process
版次1
doihttps://doi.org/10.1007/0-387-28831-7
isbn_softcover978-1-4419-3885-5
isbn_ebook978-0-387-28831-4
copyrightSpringer-Verlag US 2006
The information of publication is updating

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Shape Gradient for Image and Video Segmentationinvolving functions of parametric or non parametric probability density functions (pdfs) of image features. Among these functions, we notably study the minimization of information measures such as the entropy for the segmentation of homogeneous regions or the minimization of the distance between pdfs for tracking or matching regions of interest.
板凳
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Total Variation Image Restoration: Overview and Recent Developmentsometry and textures, in ameliorating the staircasing effect, and in exploiting the multiscale nature of the models. In addition, new computational methods have been proposed with improved computational speed and robustness. We shall review some of these recent developments.
地板
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Curve Propagation, Level Set Methods and Groupinge function that aims to account for the expected visual properties of the object, impose certain smoothness constraints and encode prior knowledge on the geometric form of the object to be recovered is presented. Promising experimental results demonstrate the potential of such a method.
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On a Stochastic Model of Geometric Snakesd unit circle, whose profile converges toward the Gauss-Minkowsky transformation of solutions of curve shortening flows initiated by convex curves The present note shows that this theory may be implemented as a new way of evolving curves as a possible alternative to level set methods.
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Image Alignment and Stitchinges between overlapping images. I then discuss various compositing options, including multi band and gradient-domain blending, as well as techniques for removing blur and ghosted images. The resulting techniques can be used to create high-quality panoramas for static or interactive viewing.
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Book 2006ing, math- ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a
10#
發(fā)表于 2025-3-23 08:58:39 | 只看該作者
s of computational visionAbstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math- ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems
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