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Favorskaya M.N., Jain L.C. (eds.) Computer Vision in Control Systems

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Favorskaya M.N., Jain L.C. (eds.) Computer Vision in Control Systems
Издательство Springer, 2015, -692 pp.
Two-volume edition.
The first volume is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The contemporary solutions based on advanced mathematical achievements emphasize more information and visual monitoring in natural and human environment. The real challenge of designing such observation models are to make them close to realistic visualization and interpretation of events in our world. The volume presents some of the research results from some of the most respectable researchers in the field of computer vision stressing on mathematical theory.
The second volume is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The contemporary solutions based on advanced mathematical achievements emphasize more information and visual monitoring in natural and human environment. The real challenge of designing such observation models is to make them close to realistic visualization and interpretation of events in our world.
This volume presents some of the research results from some of the most respectable researchers in the field of computer vision including some innovative applications in practice. The contributions include the recent methodologies for human action recognition, real-time audience analysis system, panorama construction from multiview cameras in outdoor scenes, real-time applications in robot navigation and intelligent control, adaptive surveillance algorithms, vision technologies for civil aviation, navigation of autonomous underwater vehicles, denoising algorithms for intelligent recognition systems, and image segmentation based on 2D Markov chains.
The edition is directed to the Ph.D. students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.
Volume I. Mathematical Theory
Development of Mathematical Theory in Computer Vision
Morphological Image Analysis for Computer Vision Applications
Methods for Detecting of Structural Changes in Computer Vision Systems
Hierarchical Adaptive KL-Based Transform: Algorithms and Applications
Automatic Estimation for Parameters of Image Projective Transforms Based on Object-Invariant Cores
A Way of Energy Analysis for Image and Video Sequence Processing
Optimal Measurement of Visual Motion Across Spatial and Temporal Scales
Scene Analysis Using Morphological Mathematics and Fuzzy Logic
Digital Video Stabilization in Static and Dynamic Scenes
Implementation of Hadamard Matrices for Image Processing
A Generalized Criterion of Efficiency for Telecommunication Systems
Volume II. Innovations in Practice
Practical Matters in Computer Vision
Human Action Recognition: Contour-Based and Silhouette-Based Approaches
The Application of Machine Learning Techniques to Real Time Audience Analysis System
Panorama Construction from Multi-view Cameras in Outdoor Scenes
A New Real-Time Method of Contextual Image Description and Its Application in Robot Navigation and Intelligent Control
Perception of Audio Visual Information for Mobile Robot Motion Control Systems
Adaptive Surveillance Algorithms Based on the Situation Analysis
Enhanced, Synthetic and Combined Vision Technologies for Civil Aviation
Navigation of Autonomous Underwater Vehicles Using Acoustic and Visual Data Processing
Efficient Denoising Algorithms for Intelligent Recognition Systems
Image Segmentation Based on Two-Dimensional Markov Chains
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