Applied Pattern Recognition Studies in Computational Intelligence

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. Applied Pattern Recognition......Page 1 Preface......Page 5 Contents......Page 7 Skin-based Face Detection - Extraction and Recognition of Facial Expressions......Page 12 Facial Image Processing......Page 37 Face Recognition and Pose Estimation with Parametric Linear Subspaces......Page 57 4D Segmentation of Cardiac Data Using Active Surfaces with Spatiotemporal Shape Priors......Page 83 Measuring Similarity Between Trajectories of Mobile Objects......Page 107 Matching of Hypergraphs — Algorithms, Applications, and Experiments......Page 135 Feature-Driven Emergence of Model Graphs for Object Recognition and Categorization......Page 159 A Wavelet-based Statistical Method for Chinese Writer Identification......Page 204 Texture Analysis by Accurate Identification of a Generic Markov–Gibbs Model......Page 222