更新时间：2021-06-24 16:50:46
封面
Title Page
Copyright and Credits
OpenCV 4 with Python Blueprints Second Edition
About Packt
Why subscribe?
Contributors
About the authors
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Code in Action
Download the color images
Conventions used
Get in touch
Reviews
Fun with Filters
Getting started
Planning the app
Creating a black-and-white pencil sketch
Understanding approaches for using dodging and burning techniques
Implementing a Gaussian blur with two-dimensional convolution
Applying pencil sketch transformation
Using an optimized version of a Gaussian blur
Generating a warming and cooling filter
Using color manipulation via curve shifting
Implementing a curve filter using lookup tables
Designing the warming and cooling effect
Cartoonizing an image
Using a bilateral filter for edge-aware smoothing
Detecting and emphasizing prominent edges
Combining colors and outlines to produce a cartoon
Putting it all together
Running the app
Mapping the GUI base class
Understanding the GUI constructor
Learning about a basic GUI layout
Handling video streams
Drafting a custom filter layout
Summary
Attributions
Hand Gesture Recognition Using a Kinect Depth Sensor
Setting up the app
Accessing the Kinect 3D sensor
Utilizing OpenNI-compatible sensors
Running the app and main function routine
Tracking hand gestures in real time
Understanding hand region segmentation
Finding the most prominent depth of the image center region
Applying morphological closing for smoothening
Finding connected components in a segmentation mask
Performing hand shape analysis
Determining the contour of the segmented hand region
Finding the convex hull of a contour area
Finding the convexity defects of a convex hull
Performing hand gesture recognition
Distinguishing between different causes of convexity defects
Classifying hand gestures based on the number of extended fingers
Finding Objects via Feature Matching and Perspective Transforms
Listing the tasks performed by the app
Running the app – the main() function routine
Displaying results
Understanding the process flow
Learning feature extraction
Looking at feature detection
Detecting features in an image with SURF
Obtaining feature descriptors with SURF
Understanding feature matching
Matching features across images with FLANN
Testing the ratio for outlier removal
Visualizing feature matches
Mapping homography estimation
Warping the image
Learning feature tracking
Understanding early outlier detection and rejection
Seeing the algorithm in action
3D Scene Reconstruction Using Structure from Motion
Learning about camera calibration
Understanding the pinhole camera model
Estimating the intrinsic camera parameters
Defining the camera calibration GUI
Initializing the algorithm
Collecting image and object points
Finding the camera matrix
Understanding the main routine function
