High-Dimensional and Low-Quality Visual Information Processing
From Structured Sensing and Understanding
Previously published in hardcover
Lieferzeit: Print on Demand - Lieferbar innerhalb von 3-5 Werktagen I
ISBN-13:
9783662525630
Veröffentl:
2016
Einband:
Previously published in hardcover
Seiten:
99
Autor:
Yue Deng
Gewicht:
200 g
Format:
235x156x8 mm
Serie:
Springer Theses
Sprache:
Englisch
Beschreibung:
This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing.
This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing.
Introduction.- Sparse Structure for Visual Signal Sensing.- Graph Structure for Visual Signal Sensing.- Discriminative Structure for Visual Signal Understanding.- Information Theoretic Structure for Visual Signal Understanding.- Conclusions.