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High-Dimensional and Low-Quality Visual Information Processing

Part of the Springer Theses Book Series

DOI: 10.1007/978-3-662-44526-6

ISBN: 978-3-662-44525-9

Publisher: Springer Berlin Heidelberg - Springer Journals

Sep 5, 2014

LitStream

Chapter 1Introduction

Deng, Yue

Pages: 1 –7

[This chapter provides an overview of the whole dissertation. First, we will generally review the history of computational models and visual information processing and indicate the irresistible trend of their marriage in this big data era. After introducing the low-quality properties in visual...
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Chapter 2Sparse Structure for Visual Information Sensing: Theory and Algorithms

Deng, Yue

Pages: 9 –28

[This chapter proposes to utilize sparse structure for visual information sensing and understanding. In detail, concentered on the fundamental theory of compressive sensing, we will discuss the problem of low-rank structure learning (LRSL) from sparse outliers. Different from traditional...
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Chapter 3Sparse Structure for Visual Signal Sensing: Application in 3D Reconstruction

Deng, Yue

Pages: 29 –43

[This chapter introduces a general framework to fuse noisy point clouds from multiview images of the same object. We solve this classical vision problem using a low rank structure learning model proposed in last chapter. With this framework, we construct the initial incomplete matrix from the...
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Chapter 4Graph Structure for Visual Signal Sensing

Deng, Yue

Pages: 45 –62

[Graph structure is another important structure in visual information. Concentrating on it, this chapter first presents a random-walk-based feature extraction method called commute time guided transformation (CTG) in the graph embedding framework. We introduce the usage of a robust probability...
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Chapter 5Discriminative Structure for Visual Signal Understanding

Deng, Yue

Pages: 63 –75

[This chapter presents a computational model to address one prominent psychological behavior of human beings to recognize images. The basic pursuit of our method can be concluded as that differences among multiple images help visual recognition. Generally speaking, we propose a statistical...
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Chapter 6Information-Theoretic Structure for Visual Signal Understanding

Deng, Yue

Pages: 77 –95

[In this chapter, we will investigate the performance information-theoretic structure for visual information understanding. Bag-of-feature method provides a flexible way to extract the contents of an image in a data-driven manner for visual recognition. One central task in such framework is...
LitStream

Chapter 7Conclusion

Deng, Yue

Pages: 97 –98

[This thesis sheds light on a few basic and important problems in community of visual information processing. In conclusion, the thesis successfully addressed one topic (data sensing), discussed two computational frameworks (optimization and probabilistic inference), and coped with three...

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