1. OpenCV Training course
By Theerayod Wiangtong

2. Goals
Develop a universal toolbox for research and development in the field of Computer Vision

3. Why use OpenCV?
Fast development time, more than 500 algorithms in OpenCV libraries
C/C++ based programming
Both Windows and Linux supported
Open and free, BSD license
Loads of developers using OpenCV
Loads of information and documents
Etc

4. History of OpenCV
Originally developed by Intel, currently maintained by Willow Garage

5. OpenCV - Features Cross-platform and extremely portable
Free! for both research and commercial use
Targeted for real-time applications
Table Courtesy Learning OpenCV: Computer Vision with the OpenCV Library

6. OpenCV – Architecture & Modules
CvAux
Area for experimental algorithms: e.g. HMM, Stereo vision, 3D tracking, Bg/fg segmentation, camera calibration, Shape matching, Gesture recognition, ..

7. OpenCV Comparisons

8. Examples of Using OpenCV functions
Click here

9. OpenCV: Algorithmic Content

10. (more than 500 algorithms!!)
OpenCV Functionality
Basic structures and operations
Image Analysis
Structural Analysis
Object Recognition
Motion Analysis and Object Tracking
3D Reconstruction
(more than 500 algorithms!!)

11. Image Thresholding
Fixed threshold;
Adaptive threshold;

12. Statistics min, max, mean value, standard deviation over the image
Multidimensional histograms
Norms C, L1, L2

13. Multidimensional Histograms
Histogram operations : calculation, normalization, comparison, back project

14. Histogram Equalization

15. Histograms comparison

16. Image Pyramids
Change the picture to something more clear!

17. Convolution in image
The source pixel and its surrounding pixels are all mathematically merged to produce a single destination pixel. The matrix slides across the surface of the source image, producing pixels for the destination image

18. Image Pyramids
Gaussian and Laplacian

19. Morphological Operations
Two basic morphology operations using structuring element:
erosion
dilation

20. Distance Transform
Calculate the distance for all non-feature points to the closest feature point
Two-pass algorithm, 3x3 and 5x5 masks, various metrics predefined

21. Flood Filling grayscale image, floating range
grayscale image, fixed range

22. Feature Detection
Fixed filters (Sobel operator, Canny operator, Laplacian, Scharr filter)
Hough transform (find lines and circles)

23. Edge detection operators
This means: pixel(i,j) = 2*pixel(i,j) - pixel(i,j+1) - pixel(i+1,j).
Simple
Cross 2 -1 1 -1 1 -1
Template 1: Template 2:
 pixel(i,j) = maximum(template 1, template 2)

24. Edge detection operators
Prewitt
Sobel 1 -1 1 -1 1 -1 2 -2 1 2 -1 -2
X-axis Template: Y-axis Template:
pixel(i,j) = sqrt((x-axis template)^2 + (y-axis template)^2)

25. Canny Edge Detector

26. Hough Transform

27. Another sample of using the Hough Transform
Source picture
Result

28. Contour Retrieving The contour representation:
Chain code (Freeman code)
Polygonal representation
Initial Point
Chain code for the curve:
Contour representation

29. Hierarchical representation of contours
Image Boundary
(W1)
(W2)
(W3)
(B2)
(B3)
(B4)
Get the english picture!
(W5)
(W6)

30. Contours Examples Source Picture (300x600 = 180000 pts total)
Retrieved Contours
(<1800 pts total)
After Approximation
(<180 pts total)
And it is rather fast: ~70 FPS for 640x480 on complex scenes

31. Contour Processing Approximation: RLE algorithm (chain code)
Teh-Chin approximation (polygonal)
Douglas-Peucker approximation (polygonal);
Contour moments (central and normalized up to order 3)
Matching of contours

32. Contours matching
Matching based on hierarchical representation of contours

33. Object Recognition: Eigen Image

34. Object Recognition: HMM
One person – one HMM
Stage 1 – Train every HMM
Stage 2 – Recognition
Pi - probability
Choose max(Pi) 1 … n
Get the more clear pictures! i

35. Motion Analysis and Object Tracking
Background subtraction
Motion templates
Optical flow
Active contours
Estimators

36. Background Subtraction
Background: any static or periodically moving parts of a scene that remain static or periodic over the period of interest. How about waving trees, light on/off..?!?

37. Background statistics functions
Average
Standard deviation
Connect component

38. Background Subtraction Example
Reconsider this slide!

39. Motion Templates Object silhouette Motion history images
Motion history gradients
Motion segmentation algorithm
MHG
silhouette
MHI

40. Motion Templates Example
Motion templates allow to retrieve the dynamic characteristics of the moving object

41. Object tracking Mean-shift Cam-shift:
Choose a search window (width and location)
Compute the mean of the data in the search window
Center the search window at the new mean location
Repeat until convergence
Cam-shift:
Continuously Adaptive Mean SHIFT

42. Mean shift Region of interest Center of mass Mean Shift vector
Slide by Y. Ukrainitz & B. Sarel

43. Mean shift Region of interest Center of mass Mean Shift vector
Slide by Y. Ukrainitz & B. Sarel

44. Mean shift Region of interest Center of mass Mean Shift vector
Slide by Y. Ukrainitz & B. Sarel

45. Mean shift Region of interest Center of mass Mean Shift vector
Slide by Y. Ukrainitz & B. Sarel

46. Mean shift Region of interest Center of mass Mean Shift vector
Slide by Y. Ukrainitz & B. Sarel

47. Mean shift Region of interest Center of mass Mean Shift vector
Slide by Y. Ukrainitz & B. Sarel

48. Mean shift Region of interest Center of mass
Slide by Y. Ukrainitz & B. Sarel

49. Object tracking Particle filter Optical flow, LK
Optical flow is the relation of the motion field. It is a 2D projection of the physical movement of points relative to the observer
Optical Flow
Velocity vectors

50. OpenCV shape classification capabilities
Contour approximation
Moments (image&contour)
Convexity analysis
Pair-wise geometrical histogram
Fitting functions (line, ellipse)

51. Using contours and geometry to classify shapes
Given the contour classify the geometrical figure shape (triangle, circle, etc)

52. Moments Contour moments (faster) Hu invariants
Here p is the x-order and q is the y-order, whereby order means the power to which the corresponding component is taken in the sum just displayed. E.g. m00 moment is actually just the
length in pixels of the contour.
Contour moments (faster)
Not applicable for different sizes, orientation
Hu invariants

53. Image segmentation Separate image into coherent “objects”
human segmentation

54. Segmentation Methods Edge-based approach Color segmentation: histogram
Apply edge detector (sobel, laplace, canny, gradient strokes).
Find connected components in an inverted image
Calculate the histogram. Find the objects of the selected histogram in the image.

55. OpenCV: Getting started

56. Getting Started Download OpenCV http://opencv.willowgarage.com/wiki/
There exists a short walkthrough video on YouTube at
Learning OpenCV: Computer Vision with the OpenCV Library by Gary Bradski and Adrian Kaehler

57. OpenCV 2.1 with Visual Studio 2008
Download the OpenCV Windows installer from SourceForge - "OpenCV win32-vs2008.exe".
Install it to a folder (without any spaces in it), say "C:\OpenCV2.1\". This article will refer to this path as $openCVDir
During installation, enable the option "Add OpenCV to the system PATH for all users".

58. Configure Visual Studio 2008
Open VC++ Directories configuration: Tools > Options > Projects and Solutions > VC++ Directories
Choose "Show directories for: Include files"
Add "$openCVDir\include\opencv"
Choose "Show directories for: Library files"
Add "$openCVDir\lib"
Choose "Show directories for: Source files"
Add "$openCVDir\src\cv"
Add "$openCVDir\src\cvaux"
Add "$openCVDir\src\cxcore"
Add "$openCVDir\src\highgui"

59. Configure your Project
Open Project Properties: Project > %projectName% Properties...
Open Linker Input properties: Configuration Properties > Linker > Input
Open the "..." window to edit "Additional Dependencies" and on each line put:
"cv210.lib"
"cxcore210.lib"
"highgui210.lib"
And any other lib file, e.g, cvaux.lib, necessary for your project
Your project should now build. If you get any errors try restarting Visual Studio and then doing a clean Rebuild.

60. More info http://opencv.willowgarage.com/documentation/c/index.html

61. Questions