Image Processing, Computer Vision, and Pattern Recognition

by Hamid R. Arabnia

Overview

IP, Computer Vision, and Pattern Recognition is a compendium of articles and papers that were presented at IPCV '16, an international conference that serves researchers, scholars, professionals, students, and academicians.

Product Details

ISBN-13:	9781601324429
Publisher:	CSREA
Publication date:	02/06/2017
Series:	The 2016 WorldComp International Conference Proceedings
Pages:	452
Product dimensions:	8.50(w) x 10.90(h) x 0.90(d)

About the Author

Hamid R. Arabnia is Professor, Computer Science; Editor-in-Chief, The Journal of Supercomputing (Springer); Elected Fellow, Int'l Society of Intelligent Biological Medicine (ISIBM); The University of Georgia, Department of Computer Science.

Table of Contents

IMAGING SCIENCE AND NOVEL APPLICATIONS

Manifold Transfer Subspace Learning (MTSL) for High Dimensional Data-Applications to Handwritten Digits and Health Informatics
Real-time, Quasi Immersive, High Definition Automotive 3D Surround View System
Cellular Automata Design for Digital Ornaments
Estimation of 2D and 3D Texture at Micro-Scale Using Independent Component Analysis
Surveillance using Thermal-Imaging Sensors
A Variable Circular-Shift Image-Encryption Algorithm

VIDEO PROCESSING + COMPRESSION AND APPLICATIONS

A Novel Video Matting Approach Based on Closed-Form Solutions and Probability Density Functions
A Multithreaded Robust C/C++ Implementation of Video Data Compression
Probability Based Fast Prediction by Using Inter-View Correlation for 3D Video Coding

RECOGNITION SYSTEMS, TRACKING, DETECTION, AND APPLICATIONS

Extraction of Textual Information from Images Using Mobile Devices
Face Recognition with Connecting Uniform and Center-Symmetric Local Binary Patterns in a Support Vector Machine
Triangular Road Signs Detection and Recognition Algorithm and its Embedded System Implementation
Face Sketch Synthesis: A Neural Style Approach

COMPUTER VISION, RECOGNITION AND DETECTION SYSTEMS + APPLICATIONS

An Extension to the INCA Model for Probabilistic Gestural Recognition
Automated Color Variation Flaw Inspection of LCD Panels Using Computer Vision
Dense Pixel Correspondence based Gender Recognition of Facial Images