Computer Vision Research Progress

By: Zhongkai Zhu

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Hardcover | 1 March 2008

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Hardcover
335 Pages

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26.6 x 18.8 x 2.8

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Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images. The image data can take many forms, such as a video sequence, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply the theories and models of computer vision to the construction of computer vision systems. Examples of applications of computer vision systems include systems for controlling processes (e.g. an industrial robot or an autonomous vehicle). Detecting events (e.g. for visual surveillance). Organising information (e.g. for indexing databases of images and image sequences), Modelling objects or environments (e.g. industrial inspection, medical image analysis or topographical modelling), Interaction (e.g. as the input to a device for computer-human interaction). Computer vision can also be describe

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Computer Vision Databases

Preface
Application of Stereo-Computer Vision Techniques to High Sensitivity Measurement of Shape and Deformation of Solid Bodies
A Follow-up of Image Registration Techniques For Application in Digital Subtraction Angiography
Intelligent Video Analysis for Traffic Surveillance by Perceptual Edge Feature Grouping
Accurately Calibrating Image Distortion Center of Radial Camera
Twin Object-centered Models for 3D Reconstruction
Fast Face Detector and Recognition for Biometrical Security System
Joint Rotation, Shift and Scale Invariant Feature Extraction for Content-Based Image Retrieval
Application of Computer Vision in Shortest Path Planning
Object Detection and Tracking Using Bayes-Constrained Particle Swarm Optimization
Head Pose Estimation and Multi-View Face Recognition with Nonlinear Dimensionality Reduction Methods
Evidence-Based Pixel Labeling for Color Image Segmentation
E-Quality for Manufacturing (EQM) Using Internet-based Computer Vision System
Evaluation and Assessment of Rigid, Affine, and Nonrigid Registration Techniques: Application to X-ray Angiography Images
Index
Table of Contents provided by Publisher. All Rights Reserved.

Computer Vision Research Progress

At a Glance

Hardcover

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How to return your order

Defective items

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