A Computational Framework For Segmentation And Grouping

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Author: G. Medioni
Publisher: Elsevier
ISBN: 9780080529486
Size: 67.72 MB
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A Computational Framework For Segmentation And Grouping by G. Medioni


Original Title: A Computational Framework For Segmentation And Grouping

This book represents a summary of the research we have been conducting since the early 1990s, and describes a conceptual framework which addresses some current shortcomings, and proposes a unified approach for a broad class of problems. While the framework is defined, our research continues, and some of the elements presented here will no doubt evolve in the coming years.It is organized in eight chapters. In the Introduction chapter, we present the definition of the problems, and give an overview of the proposed approach and its implementation. In particular, we illustrate the limitations of the 2.5D sketch, and motivate the use of a representation in terms of layers instead. In chapter 2, we review some of the relevant research in the literature. The discussion focuses on general computational approaches for early vision, and individual methods are only cited as references. Chapter 3 is the fundamental chapter, as it presents the elements of our salient feature inference engine, and their interaction. It introduced tensors as a way to represent information, tensor fields as a way to encode both constraints and results, and tensor voting as the communication scheme. Chapter 4 describes the feature extraction steps, given the computations performed by the engine described earlier. In chapter 5, we apply the generic framework to the inference of regions, curves, and junctions in 2-D. The input may take the form of 2-D points, with or without orientation. We illustrate the approach on a number of examples, both basic and advanced. In chapter 6, we apply the framework to the inference of surfaces, curves and junctions in 3-D. Here, the input consists of a set of 3-D points, with or without as associated normal or tangent direction. We show a number of illustrative examples, and also point to some applications of the approach. In chapter 7, we use our framework to tackle 3 early vision problems, shape from shading, stereo matching, and optical flow computation. In chapter 8, we conclude this book with a few remarks, and discuss future research directions. We include 3 appendices, one on Tensor Calculus, one dealing with proofs and details of the Feature Extraction process, and one dealing with the companion software packages.

Advances In Image And Video Segmentation

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Author: Yu-Jin Zhang
Publisher: Irm Pr
ISBN: 9781591407539
Size: 41.40 MB
Format: PDF
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Advances In Image And Video Segmentation by Yu-Jin Zhang


Original Title: Advances In Image And Video Segmentation

"This book attempts to bring together a selection of the latest results of state-of-the art research in image and video segmentation, one of the most critical tasks of image and video analysis that has the objective of extracting information (represented by data) from an image or a sequence of images (video)"--Provided by publisher

Pattern Recognition

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Author: Bernd Michaelis
Publisher: Springer
ISBN:
Size: 20.27 MB
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Pattern Recognition by Bernd Michaelis


Original Title: Pattern Recognition

This book constitutes the refereed proceedings of the 25th Symposium of the German Association for Pattern Recognition, DAGM 2003, held in Magdeburg, Germany in September 2003. The 74 revised papers presented were carefully reviewed and selected from more than 140 submissions. The papers address all current issues in pattern recognition and are organized in sections on image analyses, callibration and 3D shape, recognition, motion, biomedical applications, and applications.

Phoneme Based Speech Segmentation Using Hybrid Soft Computing Framework

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Author: Mousmita Sarma
Publisher: Springer
ISBN: 8132218620
Size: 22.51 MB
Format: PDF, ePub, Mobi
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Phoneme Based Speech Segmentation Using Hybrid Soft Computing Framework by Mousmita Sarma


Original Title: Phoneme Based Speech Segmentation Using Hybrid Soft Computing Framework

The book discusses intelligent system design using soft computing and similar systems and their interdisciplinary applications. It also focuses on the recent trends to use soft computing as a versatile tool for designing a host of decision support systems.

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