Computer Vision and Augmented Reality in iOS: OpenCV and ARKit Applications

Table of Contents
About the Author
About the Technical Reviewer
Acknowledgments
Chapter 1: Introduction to Computer Vision
	What Is Computer Vision?
	An Overview on How Computer Vision Works
	Why Do We Need Computer Vision?
	The Evolution of Computer Vision
	Traditional vs. Deep Learning–Based Computer Vision
	Computer Vision in Augmented Reality
	Summary
Chapter 2: Introduction to Augmented Reality
	What Is Augmented Reality?
	Different Types of Augmented Reality
	Summary
Chapter 3: Image and Video Processing Fundamentals
	Mathematics Overview
	Image Processing Basics
	Standard Algorithms
	Object Detection
	Summary
Chapter 4: Computer Vision Applications
	Overview
	Applications of Computer Vision
		Read, Write, and Display Images
		Change the Color Space
		Resize the Images
		Rotate the Image
		Bitwise Operation
		Detect the Edges
		Image Filtering
		Detect Face
	Computer Vision Algorithms
		Image Classification in Deep Learning
		Object Detection
		Object Detection Types
		Importance of Object Detection
		Detection of Anomaly
		Object Tracking
		Semantic Segmentation
		Vehicles That Are Automatic
		Medical Diagnostic Picture
		Instance Segmentation
		Requirements
		Work on Image Reconstruction
	Implementing Vision Applications
		A) Face Detection/Recognition
			Implementation
		B) Body Detection/Tracking
			OpenCV Tracking API
			BOOSTING Tracker
				MIL Tracker
			Kernelized Correlation Filter (KCF)
				MedianFlow Tracker
				GOTURN Tracker
				MOSSE Tracker
				CSRT Tracker
		C) Image-to-Text Analysis
			Using the C++ OCR Library, Convert an Image to Text
			Using C++ to Convert an Image Page to Text
			Using C++, Perform Single-Line OCR on an Image
			In C++, Convert a Specific Area of an Image into Text
Chapter 5: Custom Object Tracking
	Overview
	Real-Time Object Tracking
		Background
		Utilizing Code
		Libraries
		Conclusions
		Points of Concern
		Custom Barcode Generator/Reader
			Utilizing C++, Build and Read Barcodes
			API for Producing and Reading Barcodes in C++
			Generating a Barcode Using C++
			Utilizing C++, Produce a 2D Barcode (QR or Other)
			With C++, Create and Customize Barcodes
			Utilizing C++, Create Barcodes with Subtitles
			Utilizing C++, Scanning and Reading Barcodes
			C++ Is Used to Read Barcodes with Several Symbologies
	Summary
Chapter 6: Augmented Reality Using OpenCV
	Overview
		Marker-Based AR
			Marker-Less AR
		Location-Based AR
		Marker-Based Augmented Reality
			Using ArUco Markers in OpenCV (C++) to Create Augmented Reality
			What Are ArUco Markers?
			Using OpenCV to Create ArUco Markers
			An Augmented Reality Application
			Marker-Less Augmented Reality Using Visual-Inertial Estimation on a Phone
			Augmented Reality (AR) Subclass of VR
			Estimation
			ORB Function Detector
			SLAM Process
			Monocular Camera
			Key Problem
			Proposed Adaptive Visual-Inertial Approach
			Real-Time Motion Tracking
	Summary
Chapter 7: Augmented Reality Using ARKit and OpenCV
	Why Do You Use OpenCV instead of Core ML?
		Multiple Platforms Are Supported
		ARKit and OpenCV Integration
		To Sum Up
		Prerequisite
		Hardware
		Software
		Body Tracking Step by Step
		Step 1: Set Up the Primary Scenario
		Step 2: Set Up the Skeleton
		Step 3: Locate the Followed Bodies
		Step 4: Show the Skeleton
		Step 5: Create and Deploy
		Face Tracking in ARKit 3
		User Level: Basic
		Setup and Specifications for ARKit 3
		Session Objects in Augmented Reality
		Prefab AR Glasses
		ARGlassesController Class
		ARFace Data and Face Detection in ARKit 3
		Color Selector
	Summary
Index