OpenCV with Python By Example > PACKT 원서리스트

1: Applying Geometric Transformations to Images
Installing OpenCV-Python
Reading, displaying, and saving images
Image color spaces
Image translation
Image rotation
Image scaling
Affine transformations
Projective transformations
Image warping
Summary

2: Detecting Edges and Applying Image Filters
2D convolution
Blurring
Edge detection
Motion blur
Sharpening
Embossing
Erosion and dilation
Creating a vignette filter
Enhancing the contrast in an image
Summary

3: Cartoonizing an Image
Accessing the webcam
Keyboard inputs
Mouse inputs
Interacting with a live video stream
Cartoonizing an image
Summary

4: Detecting and Tracking Different Body Parts
Using Haar cascades to detect things
What are integral images?
Detecting and tracking faces
Fun with faces
Detecting eyes
Fun with eyes
Detecting ears
Detecting a mouth
It's time for a moustache
Detecting a nose
Detecting pupils
Summary

5: Extracting Features from an Image
Why do we care about keypoints?
What are keypoints?
Detecting the corners
Good Features To Track
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)
Summary

6: Creating a Panoramic Image
Matching keypoint descriptors
Creating the panoramic image
What if the images are at an angle to each other?
Summary

7: Seam Carving
Why do we care about seam carving?
How does it work?
How do we define "interesting"?
How do we compute the seams?
Can we expand an image?
Can we remove an object completely?
Summary

8: Detecting Shapes and Segmenting an Image
Contour analysis and shape matching
Approximating a contour
Identifying the pizza with the slice taken out
How to censor a shape?
What is image segmentation?
Watershed algorithm
Summary

9: Object Tracking
Frame differencing
Colorspace based tracking
Building an interactive object tracker
Feature based tracking
Background subtraction
Summary

10: 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?
Summary

11: Stereo Vision and 3D Reconstruction
What is stereo correspondence?
What is epipolar geometry?
Building the 3D map
Summary

12: Augmented Reality
What is the premise of augmented reality?
What does an augmented reality system look like?
Geometric transformations for augmented reality
What is pose estimation?
How to track planar objects?
How to augment our reality?
Let's add some movements
Summary

backindex: Appendix A: Index