Applied Pattern Recognition [electronic resource] / edited by Horst Bunke, Abraham Kandel, Mark Last.

By: Bunke, Horst [editor.]Contributor(s): Kandel, Abraham [editor.] | Last, Mark [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Computational Intelligence: 91Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Description: online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540768319Subject(s): Engineering | Artificial intelligence | Computer vision | Optical pattern recognition | Mathematics | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Pattern Recognition | Artificial Intelligence (incl. Robotics) | Computer Imaging, Vision, Pattern Recognition and Graphics | Applications of MathematicsAdditional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
Face Recognition Applications -- Skin-based Face Detection-Extraction and Recognition of Facial Expressions -- Facial Image Processing -- Face Recognition and Pose Estimation with Parametric Linear Subspaces -- Spatio-Temporal Patterns -- 4D Segmentation of Cardiac Data Using Active Surfaces with Spatiotemporal Shape Priors -- Measuring Similarity Between Trajectories of Mobile Objects -- Graph-Based Methods -- Matching of Hypergraphs — Algorithms, Applications, and Experiments -- Feature-Driven Emergence of Model Graphs for Object Recognition and Categorization -- Special Applications -- A Wavelet-based Statistical Method for Chinese Writer Identification -- Texture Analysis by Accurate Identification of a Generic Markov–Gibbs Model.
In: Springer eBooksSummary: A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.
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Face Recognition Applications -- Skin-based Face Detection-Extraction and Recognition of Facial Expressions -- Facial Image Processing -- Face Recognition and Pose Estimation with Parametric Linear Subspaces -- Spatio-Temporal Patterns -- 4D Segmentation of Cardiac Data Using Active Surfaces with Spatiotemporal Shape Priors -- Measuring Similarity Between Trajectories of Mobile Objects -- Graph-Based Methods -- Matching of Hypergraphs — Algorithms, Applications, and Experiments -- Feature-Driven Emergence of Model Graphs for Object Recognition and Categorization -- Special Applications -- A Wavelet-based Statistical Method for Chinese Writer Identification -- Texture Analysis by Accurate Identification of a Generic Markov–Gibbs Model.

A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.

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