Imagine Looking At A Picture On A Printed Page Or Computer Screen, Adjusting Your Eyes In A Manner That Most People Can Learn Easily, And Suddenly Having Objects Pop Out At You In Vivid 3D. Many People Have Already Experienced This With The Magic Eye And Related Posters That Were Massively Popular In The 90'S. But What Is Not So Well Known Is That This Single-Image Stereogram Technology Has Come A Long Way Since Those Early Days. The Big Breakthrough Came When Algorithms Were Discovered That Could Map Textures Onto The Surface Of Single-Image Stereograms. I Believe This Is The Only Available Book That Delves Deeply Into Stereogram Algorithms, Including Highly Documented C++ Source Code. These Algorithms Can Be Used To Great Effect By Artists To Create Works Of Art That Are Far Beyond The Crude Stereograms Of Yesteryear. Perhaps Even More Importantly, The Ability To Display Depth Maps In Clear Stereo Using Only A Single Printed Image Can Be Invaluable For Scientific Presentations. This Book Is An Essential Resource For Anyone Writing Programs For Stereogram Generation.

Timothy Masters Received A Phd In Mathematical Statistics With A Specialization In Numerical Computing. Since Then He Has Continuously Worked As An Independent Consultant For Government And Industry. His Early Research Involved Automated Feature Detection In High-Altitude Photographs While He Developed Applications For Flood And Drought Prediction, Detection Of Hidden Missile Silos, And Identification Of Threatening Military Vehicles. Later He Worked With Medical Researchers In The Development Of Computer Algorithms For Distinguishing Between Benign And Malignant Cells In Needle Biopsies. For The Last Twenty Years He Has Focused Primarily On Methods For Evaluating Automated Financial Market Trading Systems. He Has Authored Many Books On Applications Of Predictive Modeling: Practical Neural Network Recipes In C++ (Academic Press, 1993) Signal And Image Processing With Neural Networks (Wiley, 1994) Advanced Algorithms For Neural Networks (Wiley, 1995) Neural, Novel, And Hybrid Algorithms For Time Series Prediction (Wiley, 1995) Assessing And Improving Prediction And Classification (Createspace, 2013, Apress, 2018) Deep Belief Nets In C++ And Cuda C: Vol I: Restricted Boltzmann Machines And Supervised Feedforward Networks (Createspace, 2015, Apress, 2018) Deep Belief Nets In C++ And Cuda C: Vol Ii: Autoencoding In The Complex Domain (Createspace, 2015, Apress, 2018) Deep Belief Nets In C++ And Cuda C: Vol Iii: Convolutional Nets (Createspace, 2016, Apress, 2018) Data Mining Algorithms In C++ (Createspace, 2016, Apress, 2018) Testing And Tuning Market Trading Systems (Createspace, 2018)