Chapter
Choosing and using the right setup tools
Finding documentation, help, and updates
Chapter 2: Handling Files, Cameras,
and GUIs
An object-oriented design
Chapter 3: Filtering Images
Channel mixing – seeing in Technicolor
Curves – bending color space
Custom kernels – getting convoluted
Modifying the application
Chapter 4: Tracking Faces with
Haar Cascades
Conceptualizing Haar cascades
Getting Haar cascade data
Defining a face as a hierarchy of rectangles
Tracing, cutting, and pasting rectangles
Adding more utility functions
Modifying the application
Chapter 5: Detecting Foreground/Background Regions
and Depth
Capturing frames from a depth camera
Creating a mask from a disparity map
Modifying the application
Appendix A: Integrating with Pygame
Documentation and tutorials
Subclassing managers.WindowManager
Modifying the application
Appendix B: Generating Haar Cascades for Custom Targets
Gathering positive and negative training images
Finding the training executables
Creating the training sets and cascade
Module 2: OpenCV with Python By Example
Chapter 1: Detecting Edges and Applying Image Filters
Creating a vignette filter
Enhancing the contrast in an image
Chapter 2: Cartoonizing an Image
Interacting with a live video stream
Chapter 3: Detecting and Tracking Different Body Parts
Using Haar cascades to detect things
What are integral images?
Detecting and tracking faces
It's time for a moustache
Chapter 4: Extracting Features from
an Image
Why do we care about keypoints?
Scale Invariant Feature Transform (SIFT)
Speeded Up Robust Features (SURF)
Features from Accelerated Segment Test (FAST)
Binary Robust Independent Elementary Features (BRIEF)
Oriented FAST and Rotated BRIEF (ORB)
Chapter 5: Creating a Panoramic Image
Matching keypoint descriptors
Creating the panoramic image
What if the images are at an angle
to each other?
Why do we care about seam carving?
How do we define "interesting"?
How do we compute the seams?
Can we remove an object completely?
Chapter 7: Detecting Shapes and Segmenting an Image
Contour analysis and shape matching
Identifying the pizza with the slice
taken out
What is image segmentation?
Chapter 8: Object Tracking
Colorspace based tracking
Building an interactive object tracker
Chapter 9: Object Recognition
Object detection versus object recognition
What is a dense feature detector?
What is a visual dictionary?
What is supervised and unsupervised learning?
What are Support Vector Machines?
How do we actually implement this?
Chapter 10: Stereo Vision and 3D Reconstruction
What is stereo correspondence?
What is epipolar geometry?
Chapter 11: Augmented Reality
What is the premise of augmented reality?
What does an augmented reality system look like?
Geometric transformations for augmented reality
How to track planar objects?
How to augment our reality?
Module 3: OpenCV with Python Blueprints
Chapter 1: Fun with Filters
Creating a black-and-white pencil sketch
Generating a warming/cooling filter
Chapter 2: Hand Gesture Recognition Using a Kinect Depth Sensor
Tracking hand gestures in real time
Chapter 3: Finding Objects via
Feature Matching and Perspective Transforms
Tasks performed by the app
Seeing the algorithm in action
Chapter 4: 3D Scene Reconstruction Using Structure from Motion
Estimating the camera motion from a pair of images
3D point cloud visualization
Chapter 5: Tracking Visually Salient Objects
Chapter 6: Learning to Recognize
Traffic Signs
Chapter 7: Learning to Recognize Emotions on Faces
Facial expression recognition
OpenCV: Computer Vision Projects with Python
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